Biomarkers and methods for predicting preterm birth

ABSTRACT

The disclosure provides biomarker panels, methods and kits for determining the probability for preterm birth in a pregnant female. The present disclosure is based, in part, on the discovery that certain proteins and peptides in biological samples obtained from a pregnant female are differentially expressed in pregnant females that have an increased risk of developing in the future or presently suffering from preterm birth relative to matched controls. The present disclosure is further based, in part, on the unexpected discovery that panels combining one or more of these proteins and peptides can be utilized in methods of determining the probability for preterm birth in a pregnant female with relatively high sensitivity and specificity. These proteins and peptides disclosed herein serve as biomarkers for classifying test samples, predicting a probability of preterm birth, monitoring of progress of preterm birth in a pregnant female, either individually or in a panel of biomarkers.

This application is a continuation of application Ser. No. 16/255,757filed Jan. 23, 2019, which is a continuation of Ser. No. 15/286,486,filed Oct. 5, 2016, which is a continuation of application Ser. No.14/213,861, filed Mar. 14, 2014, which claims the benefit of U.S.provisional patent application No. 61/919,586, filed Dec. 20, 2013, andU.S. provisional application No. 61/798,504, filed Mar. 15, 2013, eachof which is incorporated herein by reference in its entirety.

This application incorporates by reference a Sequence Listing submittedherewith as an ASCII text file entitled 13271-060-999_SL.txt created onJun. 19, 2021, and having a size of 216,425 bytes.

The invention relates generally to the field of personalized medicineand, more specifically to compositions and methods for determining theprobability for preterm birth in a pregnant female.

BACKGROUND

According to the World Health Organization, an estimated 15 millionbabies are born preterm (before 37 completed weeks of gestation) everyyear. In almost all countries with reliable data, preterm birth ratesare increasing. See, World Health Organization; March of Dimes; ThePartnership for Maternal, Newborn & Child Health; Save the Children,Born too soon: the global action report on preterm birth, ISBN9789241503433(2012). An estimated 1 million babies die annually frompreterm birth complications. Globally, preterm birth is the leadingcause of newborn deaths (babies in the first four weeks of life) and thesecond leading cause of death after pneumonia in children under fiveyears. Many survivors face a lifetime of disability, including learningdisabilities and visual and hearing problems.

Across 184 countries with reliable data, the rate of preterm birthranges from 5% to 18% of babies born. Blencowe et al., “National,regional and worldwide estimates of preterm birth.” The Lancet, 9;379(9832):2162-72 (2012). While over 60% of preterm births occur inAfrica and south Asia, preterm birth is nevertheless a global problem.Countries with the highest numbers include Brazil, India, Nigeria andthe United States of America. Of the 11 countries with preterm birthrates over 15%, all but two are in sub-Saharan Africa. In the poorestcountries, on average, 12% of babies are born too soon compared with 9%in higher-income countries. Within countries, poorer families are athigher risk. More than three-quarters of premature babies can be savedwith feasible, cost-effective care, for example, antenatal steroidinjections given to pregnant women at risk of preterm labour tostrengthen the babies' lungs.

Infants born preterm are at greater risk than infants born at term formortality and a variety of health and developmental problems.Complications include acute respiratory, gastrointestinal, immunologic,central nervous system, hearing, and vision problems, as well aslonger-term motor, cognitive, visual, hearing, behavioral,social-emotional, health, and growth problems. The birth of a preterminfant can also bring considerable emotional and economic costs tofamilies and have implications for public-sector services, such ashealth insurance, educational, and other social support systems. Thegreatest risk of mortality and morbidity is for those infants born atthe earliest gestational ages. However, those infants born nearer toterm represent the greatest number of infants born preterm and alsoexperience more complications than infants born at term.

To prevent preterm birth in women who are less than 24 weeks pregnantwith an ultrasound showing cervical opening, a surgical procedure knownas cervical cerclage can be employed in which the cervix is stitchedclosed with strong sutures. For women less than 34 weeks pregnant and inactive preterm labor, hospitalization may be necessary as well as theadministration of medications to temporarily halt preterm labor and/orpromote the fetal lung development. If a pregnant women is determined tobe at risk for preterm birth, health care providers can implementvarious clinical strategies that may include preventive medications, forexample, hydroxyprogesterone caproate (Makena) injections and/or vaginalprogesterone gel, cervical pessaries, restrictions on sexual activityand/or other physical activities, and alterations of treatments forchronic conditions, such as diabetes and high blood pressure, thatincrease the risk of preterm labor.

There is a great need to identify and provide women at risk for pretermbirth with proper antenatal care. Women identified as high-risk can bescheduled for more intensive antenatal surveillance and prophylacticinterventions. Current strategies for risk assessment are based on theobstetric and medical history and clinical examination, but thesestrategies are only able to identify a small percentage of women who areat risk for preterm delivery. Reliable early identification of risk forpreterm birth would enable planning appropriate monitoring and clinicalmanagement to prevent preterm delivery. Such monitoring and managementmight include: more frequent prenatal care visits, serial cervicallength measurements, enhanced education regarding signs and symptoms ofearly preterm labor, lifestyle interventions for modifiable riskbehaviors, cervical pessaries and progesterone treatment. Finally,reliable antenatal identification of risk for preterm birth also iscrucial to cost-effective allocation of monitoring resources.

The present invention addresses this need by providing compositions andmethods for determining whether a pregnant woman is at risk for pretermbirth. Related advantages are provided as well.

SUMMARY

The present invention provides compositions and methods for predictingthe probability of preterm birth in a pregnant female.

In one aspect, the invention provides a panel of isolated biomarkerscomprising N of the biomarkers listed in Tables 1 through 63. In someembodiments, N is a number selected from the group consisting of 2 to24. In additional embodiments, the biomarker panel comprises at leasttwo of the isolated biomarkers selected from the group consisting ofAFTECCVVASQLR, ELLESYIDGR, and ITLPDFTGDLR. In additional embodiments,the biomarker panel comprises at least two of the isolated biomarkersselected from the group consisting of FLNWIK, FGFGGSTDSGPIR, LLELTGPK,VEHSDLSFSK, IEGNLIFDPNNYLPK, ALVLELAK, TQILEWAAER, DVLLLVHNLPQNLPGYFWYK,SEPRPGVLLR, ITQDAQLK, ALDLSLK, WWGGQPLWITATK, and LSETNR

In further embodiments, the biomarker panel comprises at least two ofthe isolated biomarkers selected from the group consisting of thebiomarkers set forth in Table 50 and the biomarkers set forth in Table52.

In a further aspect, the invention provides a panel of isolatedbiomarkers comprising N of the biomarkers listed in Tables 1 through 63.In some embodiments, N is a number selected from the group consisting of2 to 24. In additional embodiments, the biomarker panel comprises atleast two of the isolated biomarkers selected from the group consistingof the biomarkers set forth in Table 50 and the biomarkers set forth inTable 52.

In some embodiments, the invention provides a biomarker panel comprisingat least two of the isolated biomarkers selected from the groupconsisting of lipopolysaccharide-binding protein (LBP), prothrombin(THRB), complement component C5 (C5 or CO5), plasminogen (PLMN), andcomplement component C8 gamma chain (C8G or CO8G).

In some embodiments, the invention provides a biomarker panel comprisingat least two of the isolated biomarkers selected from the groupconsisting of Alpha-1B-glycoprotein (A1BG), Disintegrin andmetalloproteinase domain-containing protein 12 (ADA12), ApolipoproteinB-100 (APOB), Beta-2-microglobulin (B2MG), CCAAT/enhancer-bindingprotein alpha/beta (HP8 Peptide), Corticosteroid-binding globulin (CBG),Complement component C6, Endoglin (EGLN), Ectonucleotidepyrophosphatase/phosphodiesterase family member 2 (ENPP2), Coagulationfactor VII (FA7), Hyaluronan-binding protein 2 (HABP2),Pregnancy-specific beta-1-glycoprotein 9 (PSG9), Inhibin beta E chain(INHBE).

In other embodiments, the invention provides a biomarker panelcomprising lipopolysaccharide-binding protein (LBP), prothrombin (THRB),complement component C5 (C5 or CO5), plasminogen (PLMN), complementcomponent C8 gamma chain (C8G or CO8G), complement component 1, qsubcomponent, B chain (C1QB), fibrinogen beta chain (FIBB or FIB),C-reactive protein (CRP), inter-alpha-trypsin inhibitor heavy chain H4(ITIH4), chorionic somatomammotropin hormone (CSH), and angiotensinogen(ANG or ANGT).

In other embodiments, the invention provides a biomarker panelcomprising Alpha-1B-glycoprotein (A1BG), Disintegrin andmetalloproteinase domain-containing protein 12 (ADA12), ApolipoproteinB-100 (APOB), Beta-2-microglobulin (B2MG), CCAAT/enhancer-bindingprotein alpha/beta (HP8 Peptide), Corticosteroid-binding globulin (CBG),Complement component C6, Endoglin (EGLN), Ectonucleotidepyrophosphatase/phosphodiesterase family member 2 (ENPP2), Coagulationfactor VII (FA7), Hyaluronan-binding protein 2 (HABP2),Pregnancy-specific beta-1-glycoprotein 9 (PSG9), Inhibin beta E chain(INHBE).

In additional embodiments, the invention provides a biomarker panelcomprising at least two of the isolated biomarkers selected from thegroup consisting of the biomarkers set forth in Table 51 and thebiomarkers set forth in Table 53.

Also provided by the invention is a method of determining probabilityfor preterm birth in a pregnant female comprising detecting a measurablefeature of each of N biomarkers selected from the biomarkers listed inTables 1 through 63 in a biological sample obtained from the pregnantfemale, and analyzing the measurable feature to determine theprobability for preterm birth in the pregnant female. In someembodiments, the invention provides a method of predicting GAB, themethod encompassing detecting a measurable feature of each of Nbiomarkers selected from the biomarkers listed in Tables 1 through 63 ina biological sample obtained from a pregnant female, and analyzing saidmeasurable feature to predict GAB.

In some embodiments, a measurable feature comprises fragments orderivatives of each of the N biomarkers selected from the biomarkerslisted in Tables 1 through 63. In some embodiments of the disclosedmethods detecting a measurable feature comprises quantifying an amountof each of N biomarkers selected from the biomarkers listed in Tables 1through 63, combinations or portions and/or derivatives thereof in abiological sample obtained from the pregnant female. In additionalembodiments, the disclosed methods of determining probability forpreterm birth in a pregnant female further encompass detecting ameasurable feature for one or more risk indicia associated with pretermbirth.

In some embodiments, the disclosed methods of determining probabilityfor preterm birth in a pregnant female and related methods disclosedherein comprise detecting a measurable feature of each of N biomarkers,wherein N is selected from the group consisting of 2 to 24. In furtherembodiments, the disclosed methods of determining probability forpreterm birth in a pregnant female and related methods disclosed hereincomprise detecting a measurable feature of each of at least two isolatedbiomarkers selected from the group consisting of AFTECCVVASQLR,ELLESYIDGR, and ITLPDFTGDLR. In further embodiments, the disclosedmethods of determining probability for preterm birth in a pregnantfemale and related methods disclosed herein comprise detecting ameasurable feature of each of at least two isolated biomarkers selectedfrom the group consisting of FLNWIK, FGFGGSTDSGPIR, LLELTGPK,VEHSDLSFSK, IEGNLIFDPNNYLPK, ALVLELAK, TQILEWAAER, DVLLLVHNLPQNLPGYFWYK,SEPRPGVLLR, ITQDAQLK, ALDLSLK, WWGGQPLWITATK, and LSETNR. In furtherembodiments, the disclosed methods of determining probability forpreterm birth in a pregnant female and related methods disclosed hereincomprise detecting a measurable feature of each of at least two isolatedbiomarkers selected from the group consisting of the biomarkers setforth in Table 50 and the biomarkers set forth in Table 52.

In other embodiments, the disclosed methods of determining probabilityfor preterm birth in a pregnant female comprise detecting a measurablefeature of each of at least two isolated biomarkers selected from thegroup consisting of lipopolysaccharide-binding protein (LBP),prothrombin (THRB), complement component C5 (C5 or CO5), plasminogen(PLMN), and complement component C8 gamma chain (C8G or CO8G).

In other embodiments, the disclosed methods of determining probabilityfor preterm birth in a pregnant female comprise detecting a measurablefeature of each of at least two isolated biomarkers selected from thegroup consisting of Alpha-1B-glycoprotein (A1BG), Disintegrin andmetalloproteinase domain-containing protein 12 (ADA12), ApolipoproteinB-100 (APOB), Beta-2-microglobulin (B2MG), CCAAT/enhancer-bindingprotein alpha/beta (HP8 Peptide), Corticosteroid-binding globulin (CBG),Complement component C6, Endoglin (EGLN), Ectonucleotidepyrophosphatase/phosphodiesterase family member 2 (ENPP2), Coagulationfactor VII (FA7), Hyaluronan-binding protein 2 (HABP2),Pregnancy-specific beta-1-glycoprotein 9 (PSG9), Inhibin beta E chain(INHBE).

In further embodiments, the disclosed methods of determining probabilityfor preterm birth in a pregnant female comprise detecting a measurablefeature of each of at least two isolated biomarkers selected from thegroup consisting of lipopolysaccharide-binding protein (LBP),prothrombin (THRB), complement component C5 (C5 or CO5), plasminogen(PLMN), complement component C8 gamma chain (C8G or CO8G), complementcomponent 1, q subcomponent, B chain (C1QB), fibrinogen beta chain (FIBBor FIB), C-reactive protein (CRP), inter-alpha-trypsin inhibitor heavychain H4 (ITIH4), chorionic somatomammotropin hormone (CSH), andangiotensinogen (ANG or ANGT).

In further embodiments, the disclosed methods of determining probabilityfor preterm birth in a pregnant female comprise detecting a measurablefeature of each of at least two isolated biomarkers selected from thegroup consisting of the biomarkers set forth in Table 51 and thebiomarkers set forth in Table 53.

In some embodiments of the methods of determining probability forpreterm birth in a pregnant female, the probability for preterm birth inthe pregnant female is calculated based on the quantified amount of eachof N biomarkers selected from the biomarkers listed in Tables 1 through63. In some embodiments, the disclosed methods for determining theprobability of preterm birth encompass detecting and/or quantifying oneor more biomarkers using mass spectrometry, a capture agent or acombination thereof.

In some embodiments, the disclosed methods of determining probabilityfor preterm birth in a pregnant female encompass an initial step ofproviding a biomarker panel comprising N of the biomarkers listed inTables 1 through 63. In additional embodiments, the disclosed methods ofdetermining probability for preterm birth in a pregnant female encompassan initial step of providing a biological sample from the pregnantfemale.

In some embodiments, the disclosed methods of determining probabilityfor preterm birth in a pregnant female encompass communicating theprobability to a health care provider. In additional embodiments, thecommunication informs a subsequent treatment decision for the pregnantfemale. In further embodiments, the treatment decision of one or moreselected from the group of consisting of more frequent prenatal carevisits, serial cervical length measurements, enhanced educationregarding signs and symptoms of early preterm labor, lifestyleinterventions for modifiable risk behaviors and progesterone treatment.

In further embodiments, the disclosed methods of determining probabilityfor preterm birth in a pregnant female encompass analyzing themeasurable feature of one or more isolated biomarkers using a predictivemodel. In some embodiments of the disclosed methods, a measurablefeature of one or more isolated biomarkers is compared with a referencefeature.

In additional embodiments, the disclosed methods of determiningprobability for preterm birth in a pregnant female encompass using oneor more analyses selected from a linear discriminant analysis model, asupport vector machine classification algorithm, a recursive featureelimination model, a prediction analysis of microarray model, a logisticregression model, a CART algorithm, a flex tree algorithm, a LARTalgorithm, a random forest algorithm, a MART algorithm, a machinelearning algorithm, a penalized regression method, and a combinationthereof. In one embodiment, the disclosed methods of determiningprobability for preterm birth in a pregnant female encompass logisticregression.

In some embodiments, the invention provides a method of determiningprobability for preterm birth in a pregnant female, the methodencompassing quantifying in a biological sample obtained from thepregnant female an amount of each of N biomarkers selected from thebiomarkers listed in Tables 1 through 63; multiplying the amount by apredetermined coefficient, and determining the probability for pretermbirth in the pregnant female comprising adding the individual productsto obtain a total risk score that corresponds to the probability

In additional embodiments, the invention provides a method of predictingGAB, the method comprising: (a) quantifying in a biological sampleobtained from said pregnant female an amount of each of N biomarkersselected from the biomarkers listed in Tables 1 through 63; (b)multiplying or thresholding said amount by a predetermined coefficient,(c) determining the predicted GAB birth in said pregnant femalecomprising adding said individual products to obtain a total risk scorethat corresponds to said predicted GAB.

In further embodiments, the invention provides a method of predictingtime to birth in a pregnant female, the method comprising: (a) obtaininga biological sample from said pregnant female; (b) quantifying an amountof each of N biomarkers selected from the biomarkers listed in Tables 1through 63 in said biological sample; (c) multiplying or thresholdingsaid amount by a predetermined coefficient, (d) determining predictedGAB in said pregnant female comprising adding said individual productsto obtain a total risk score that corresponds to said predicted GAB; and(e) subtracting the estimated gestational age (GA) at time biologicalsample was obtained from the predicted GAB to predict time to birth insaid pregnant female.

Other features and advantages of the invention will be apparent from thedetailed description, and from the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1. Scatterplot of actual gestational age at birth versus predictedgestational age from random forest regression model.

FIG. 2. Distribution of predicted gestational age from random forestregression model versus actual gestational age at birth (GAB), whereactual GAB is given in categories of (i) less than 37 weeks, (ii) 37 to39 weeks, and (iii) 40 weeks or greater (peaks left to right,respectively).

DETAILED DESCRIPTION

The present disclosure is based, in part, on the discovery that certainproteins and peptides in biological samples obtained from a pregnantfemale are differentially expressed in pregnant females that have anincreased risk of preterm birth relative to controls. The presentdisclosure is further based, in part, on the unexpected discovery thatpanels combining one or more of these proteins and peptides can beutilized in methods of determining the probability for preterm birth ina pregnant female with high sensitivity and specificity. These proteinsand peptides disclosed herein serve as biomarkers for classifying testsamples, predicting probability of preterm birth, predicting probabilityof term birth, predicting gestational age at birth (GAB), predictingtime to birth and/or monitoring of progress of preventative therapy in apregnant female, either individually or in a panel of biomarkers.

The disclosure provides biomarker panels, methods and kits fordetermining the probability for preterm birth in a pregnant female. Onemajor advantage of the present disclosure is that risk of developingpreterm birth can be assessed early during pregnancy so that appropriatemonitoring and clinical management to prevent preterm delivery can beinitiated in a timely fashion. The present invention is of particularbenefit to females lacking any risk factors for preterm birth and whowould not otherwise be identified and treated.

By way of example, the present disclosure includes methods forgenerating a result useful in determining probability for preterm birthin a pregnant female by obtaining a dataset associated with a sample,where the dataset at least includes quantitative data about biomarkersand panels of biomarkers that have been identified as predictive ofpreterm birth, and inputting the dataset into an analytic process thatuses the dataset to generate a result useful in determining probabilityfor preterm birth in a pregnant female. As described further below, thisquantitative data can include amino acids, peptides, polypeptides,proteins, nucleotides, nucleic acids, nucleosides, sugars, fatty acids,steroids, metabolites, carbohydrates, lipids, hormones, antibodies,regions of interest that serve as surrogates for biologicalmacromolecules and combinations thereof.

In addition to the specific biomarkers identified in this disclosure,for example, by accession number in a public database, sequence, orreference, the invention also contemplates use of biomarker variantsthat are at least 90% or at least 95% or at least 97% identical to theexemplified sequences and that are now known or later discovered andthat have utility for the methods of the invention. These variants mayrepresent polymorphisms, splice variants, mutations, and the like. Inthis regard, the instant specification discloses multiple art-knownproteins in the context of the invention and provides exemplaryaccession numbers associated with one or more public databases as wellas exemplary references to published journal articles relating to theseart-known proteins. However, those skilled in the art appreciate thatadditional accession numbers and journal articles can easily beidentified that can provide additional characteristics of the disclosedbiomarkers and that the exemplified references are in no way limitingwith regard to the disclosed biomarkers. As described herein, varioustechniques and reagents find use in the methods of the presentinvention. Suitable samples in the context of the present inventioninclude, for example, blood, plasma, serum, amniotic fluid, vaginalsecretions, saliva, and urine. In some embodiments, the biologicalsample is selected from the group consisting of whole blood, plasma, andserum. In a particular embodiment, the biological sample is serum. Asdescribed herein, biomarkers can be detected through a variety of assaysand techniques known in the art. As further described herein, suchassays include, without limitation, mass spectrometry (MS)-based assays,antibody-based assays as well as assays that combine aspects of the two.

Protein biomarkers associated with the probability for preterm birth ina pregnant female include, but are not limited to, one or more of theisolated biomarkers listed in Tables 1 through 63. In addition to thespecific biomarkers, the disclosure further includes biomarker variantsthat are about 90%, about 95%, or about 97% identical to the exemplifiedsequences. Variants, as used herein, include polymorphisms, splicevariants, mutations, and the like.

Additional markers can be selected from one or more risk indicia,including but not limited to, maternal characteristics, medical history,past pregnancy history, and obstetrical history. Such additional markerscan include, for example, previous low birth weight or preterm delivery,multiple 2nd trimester spontaneous abortions, prior first trimesterinduced abortion, familial and intergenerational factors, history ofinfertility, nulliparity, placental abnormalities, cervical and uterineanomalies, short cervical length measurements, gestational bleeding,intrauterine growth restriction, in utero diethylstilbestrol exposure,multiple gestations, infant sex, short stature, low prepregnancy weight,low or high body mass index, diabetes, hypertension, urogenitalinfections (i.e. urinary tract infection), asthma, anxiety anddepression, asthma, hypertension, hypothyroidism. Demographic riskindicia for preterm birth can include, for example, maternal age,race/ethnicity, single marital status, low socioeconomic status,maternal age, employment-related physical activity, occupationalexposures and environment exposures and stress. Further risk indicia caninclude, inadequate prenatal care, cigarette smoking, use of marijuanaand other illicit drugs, cocaine use, alcohol consumption, caffeineintake, maternal weight gain, dietary intake, sexual activity duringlate pregnancy and leisure-time physical activities. (Preterm Birth:Causes, Consequences, and Prevention, Institute of Medicine (US)Committee on Understanding Premature Birth and Assuring HealthyOutcomes; Behrman RE, Butler AS, editors. Washington (DC): NationalAcademies Press (US); 2007). Additional risk indicia useful for asmarkers can be identified using learning algorithms known in the art,such as linear discriminant analysis, support vector machineclassification, recursive feature elimination, prediction analysis ofmicroarray, logistic regression, CART, FlexTree, LART, random forest,MART, and/or survival analysis regression, which are known to those ofskill in the art and are further described herein.

Provided herein are panels of isolated biomarkers comprising N of thebiomarkers selected from the group listed in Tables 1 through 63. In thedisclosed panels of biomarkers N can be a number selected from the groupconsisting of 2 to 24. In the disclosed methods, the number ofbiomarkers that are detected and whose levels are determined, can be 1,or more than 1, such as 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 12, 14, 15,16, 17, 18, 19, 20, 21, 22, 23, 24, 25 or more. In certain embodiments,the number of biomarkers that are detected, and whose levels aredetermined, can be 1, or more than 1, such as 2, 3, 4, 5, 6, 7, 8, 9,10, or more. The methods of this disclosure are useful for determiningthe probability for preterm birth in a pregnant female.

While certain of the biomarkers listed in Tables 1 through 63 are usefulalone for determining the probability for preterm birth in a pregnantfemale, methods are also described herein for the grouping of multiplesubsets of the biomarkers that are each useful as a panel of three ormore biomarkers. In some embodiments, the invention provides panelscomprising N biomarkers, wherein N is at least three biomarkers. Inother embodiments, N is selected to be any number from 3-23 biomarkers.

In yet other embodiments, N is selected to be any number from 2-5, 2-10,2-15, 2-20, or 2-23. In other embodiments, N is selected to be anynumber from 3-5, 3-10, 3-15, 3-20, or 3-23. In other embodiments, N isselected to be any number from 4-5, 4-10, 4-15, 4-20, or 4-23. In otherembodiments, N is selected to be any number from 5-10, 5-15, 5-20, or5-23. In other embodiments, N is selected to be any number from 6-10,6-15, 6-20, or 6-23. In other embodiments, N is selected to be anynumber from 7-10, 7-15, 7-20, or 7-23. In other embodiments, N isselected to be any number from 8-10, 8-15, 8-20, or 8-23. In otherembodiments, N is selected to be any number from 9-10, 9-15, 9-20, or9-23. In other embodiments, N is selected to be any number from 10-15,10-20, or 10-23. It will be appreciated that N can be selected toencompass similar, but higher order, ranges.

In certain embodiments, the panel of isolated biomarkers comprises oneor more, two or more, three or more, four or more, or five isolatedbiomarkers comprising an amino acid sequence selected fromAFTECCVVASQLR, ELLESYIDGR, ITLPDFTGDLR, TDAPDLPEENQAR and SFRPFVPR. Insome embodiments, the panel of isolated biomarkers comprises one ormore, two or more, three or more, four or more, or five isolatedbiomarkers comprising an amino acid sequence selected from FLNWIK,FGFGGSTDSGPIR, LLELTGPK, VEHSDLSFSK, IEGNLIFDPNNYLPK, ALVLELAK,TQILEWAAER, DVLLLVHNLPQNLPGYFWYK, SEPRPGVLLR, ITQDAQLK, ALDLSLK,WWGGQPLWITATK, and LSETNR.

In some embodiments, the panel of isolated biomarkers comprises one ormore, two or more, or three of the isolated biomarkers consisting of anamino acid sequence selected from AFTECCVVASQLR, ELLESYIDGR, andITLPDFTGDLR. In some embodiments, the panel of isolated biomarkerscomprises one or more, two or more, or three of the isolated biomarkersconsisting of an amino acid sequence selected from FLNWIK,FGFGGSTDSGPIR, LLELTGPK, VEHSDLSFSK, IEGNLIFDPNNYLPK, ALVLELAK,TQILEWAAER, DVLLLVHNLPQNLPGYFWYK, SEPRPGVLLR, ITQDAQLK, ALDLSLK,WWGGQPLWITATK, and LSETNR.

In some embodiments, the panel of isolated biomarkers comprises one ormore, two or more, or three of the isolated biomarkers consisting of anamino acid sequence selected from the biomarkers set forth in Table 50and the biomarkers set forth in Table 52.

In some embodiments, the panel of isolated biomarkers comprises one ormore peptides comprising a fragment from lipopolysaccharide-bindingprotein (LBP), Schumann et al., Science 249 (4975), 1429-1431 (1990)(UniProtKB/Swiss-Prot: P18428.3); prothrombin (THRB), Walz et al., Proc.Natl. Acad. Sci. U.S.A. 74 (5), 1969-1972(1977) (NCBI ReferenceSequence: NP_000497.1); complement component C5 (C5 or CO5) Haviland, J.Immunol. 146 (1), 362-368 (1991) (GenBank: AAA51925.1); plasminogen(PLMN) Petersen et al., J. Biol. Chem. 265 (11), 6104-6111(1990) (NCBIReference Sequences: NP_000292.1 NP_001161810.1); and complementcomponent C8 gamma chain (C8G or CO8G), Haefliger et al., Mol. Immunol.28 (1-2), 123-131 (1991) (NCBI Reference Sequence: NP_000597.2).

In some embodiments, the panel of isolated biomarkers comprises one ormore peptides comprising a fragment from cell adhesion molecule withhomology to complement component 1, q subcomponent, B chain (C1QB),Reid, Biochem. J. 179 (2), 367-371 (1979) (NCBI Reference Sequence:NP_000482.3); fibrinogen beta chain (FIBB or FIB); Watt et al.,Biochemistry 18 (1), 68-76 (1979) (NCBI Reference Sequences:NP_001171670.1 and NP_005132.2); C-reactive protein (CRP), Oliveira etal., J. Biol. Chem. 254 (2), 489-502 (1979) (NCBI Reference Sequence:NP_000558.2); inter-alpha-trypsin inhibitor heavy chain H4 (ITIH4) Kimet al., Mol. Biosyst. 7 (5), 1430-1440 (2011) (NCBI Reference Sequences:NP_001159921.1 and NP_002209.2); chorionic somatomammotropin hormone(CSH) Selby et al., J. Biol. Chem. 259 (21), 13131-13138 (1984) (NCBIReference Sequence: NP_001308.1); and angiotensinogen (ANG or ANGT)Underwood et al., Metabolism 60(8):1150-7 (2011) (NCBI ReferenceSequence: NP_000020.1).

In additional embodiments, the invention provides a panel of isolatedbiomarkers comprising N of the biomarkers listed in Tables 1 through 63.In some embodiments, N is a number selected from the group consisting of2 to 24. In additional embodiments, the biomarker panel comprises atleast two of the isolated biomarkers selected from the group consistingof AFTECCVVASQLR, ELLESYIDGR, and ITLPDFTGDLR. In additionalembodiments, the biomarker panel comprises at least two of the isolatedbiomarkers selected from the group consisting of AFTECCVVASQLR,ELLESYIDGR, ITLPDFTGDLR, TDAPDLPEENQAR and SFRPFVPR. In additionalembodiments, the biomarker panel comprises at least two of the isolatedbiomarkers selected from the group consisting of FLNWIK, FGFGGSTDSGPIR,LLELTGPK, VEHSDLSFSK, IEGNLIFDPNNYLPK, ALVLELAK, TQILEWAAER,DVLLLVHNLPQNLPGYFWYK, SEPRPGVLLR, ITQDAQLK, ALDLSLK, WWGGQPLWITATK, andLSETNR.

In additional embodiments, the biomarker panel comprises at least two ofthe isolated biomarkers selected from the group consisting of thebiomarkers set forth in Table 50 and the biomarkers set forth in Table52.

In further embodiments, the biomarker panel comprises at least two ofthe isolated biomarkers selected from the group consisting oflipopolysaccharide-binding protein (LBP), prothrombin (THRB), complementcomponent C5 (C5 or CO5), plasminogen (PLMN), and complement componentC8 gamma chain (C8G or CO8G). In another embodiment, the inventionprovides a biomarker panel comprising at least three isolated biomarkersselected from the group consisting of lipopolysaccharide-binding protein(LBP), prothrombin (THRB), complement component C5 (C5 or CO5),plasminogen (PLMN), and complement component C8 gamma chain (C8G orCO8G).

In further embodiments, the biomarker panel comprises at least two ofthe isolated biomarkers selected from the group consisting ofAlpha-1B-glycoprotein (A1BG), Disintegrin and metalloproteinasedomain-containing protein 12 (ADA12), Apolipoprotein B-100 (APOB),Beta-2-microglobulin (B2MG), CCAAT/enhancer-binding protein alpha/beta(HP8 Peptide), Corticosteroid-binding globulin (CBG), Complementcomponent C6, Endoglin (EGLN), Ectonucleotidepyrophosphatase/phosphodiesterase family member 2 (ENPP2), Coagulationfactor VII (FA7), Hyaluronan-binding protein 2 (HABP2),Pregnancy-specific beta-1-glycoprotein 9 (PSG9), Inhibin beta E chain(INHBE).

In some embodiments, the invention provides a biomarker panel comprisinglipopolysaccharide-binding protein (LBP), prothrombin (THRB), complementcomponent C5 (C5 or CO5), plasminogen (PLMN), complement component C8gamma chain (C8G or CO8G), complement component 1, q subcomponent, Bchain (C1QB), fibrinogen beta chain (FIBB or FIB), C-reactive protein(CRP), inter-alpha-trypsin inhibitor heavy chain H4 (ITIH4), chorionicsomatomammotropin hormone (CSH), and angiotensinogen (ANG or ANGT). Insome embodiments, the invention provides a biomarker panel comprisingAlpha-1B-glycoprotein (A1BG), Disintegrin and metalloproteinasedomain-containing protein 12 (ADA12), Apolipoprotein B-100 (APOB),Beta-2-microglobulin (B2MG), CCAAT/enhancer-binding protein alpha/beta(HP8 Peptide), Corticosteroid-binding globulin (CBG), Complementcomponent C6, Endoglin (EGLN), Ectonucleotidepyrophosphatase/phosphodiesterase family member 2 (ENPP2), Coagulationfactor VII (FA7), Hyaluronan-binding protein 2 (HABP2),Pregnancy-specific beta-1-glycoprotein 9 (PSG9), Inhibin beta E chain(INHBE).

In another aspect, the invention provides a biomarker panel comprisingat least two isolated biomarkers selected from the group consisting oflipopolysaccharide-binding protein (LBP), prothrombin (THRB), complementcomponent C5 (C5 or CO5), plasminogen (PLMN), complement component C8gamma chain (C8G or CO8G), complement component 1, q subcomponent, Bchain (C1QB), fibrinogen beta chain (FIBB or FIB), C-reactive protein(CRP), inter-alpha-trypsin inhibitor heavy chain H4 (ITIH4), chorionicsomatomammotropin hormone (CSH), and angiotensinogen (ANG or ANGT) andthe biomarkers set forth in Tables 51 and 53.

In another aspect, the invention provides a biomarker panel comprisingat least two isolated biomarkers selected from the group consisting ofAlpha-1B-glycoprotein (A1BG), Disintegrin and metalloproteinasedomain-containing protein 12 (ADA12), Apolipoprotein B-100 (APOB),Beta-2-microglobulin (B2MG), CCAAT/enhancer-binding protein alpha/beta(HP8 Peptide), Corticosteroid-binding globulin (CBG), Complementcomponent C6, Endoglin (EGLN), Ectonucleotidepyrophosphatase/phosphodiesterase family member 2 (ENPP2), Coagulationfactor VII (FA7), Hyaluronan-binding protein 2 (HABP2),Pregnancy-specific beta-1-glycoprotein 9 (PSG9), Inhibin beta E chain(INHBE).

It must be noted that, as used in this specification and the appendedclaims, the singular forms “a”, “an” and “the” include plural referentsunless the content clearly dictates otherwise. Thus, for example,reference to “a biomarker” includes a mixture of two or more biomarkers,and the like.

The term “about,” particularly in reference to a given quantity, ismeant to encompass deviations of plus or minus five percent.

As used in this application, including the appended claims, the singularforms “a,” “an,” and “the” include plural references, unless the contentclearly dictates otherwise, and are used interchangeably with “at leastone” and “one or more.”

As used herein, the terms “comprises,” “comprising,” “includes,”“including,” “contains,” “containing,” and any variations thereof, areintended to cover a non-exclusive inclusion, such that a process,method, product-by-process, or composition of matter that comprises,includes, or contains an element or list of elements does not includeonly those elements but can include other elements not expressly listedor inherent to such process, method, product-by-process, or compositionof matter.

As used herein, the term “panel” refers to a composition, such as anarray or a collection, comprising one or more biomarkers. The term canalso refer to a profile or index of expression patterns of one or morebiomarkers described herein. The number of biomarkers useful for abiomarker panel is based on the sensitivity and specificity value forthe particular combination of biomarker values.

As used herein, and unless otherwise specified, the terms “isolated” and“purified” generally describes a composition of matter that has beenremoved from its native environment (e.g., the natural environment if itis naturally occurring), and thus is altered by the hand of man from itsnatural state. An isolated protein or nucleic acid is distinct from theway it exists in nature.

The term “biomarker” refers to a biological molecule, or a fragment of abiological molecule, the change and/or the detection of which can becorrelated with a particular physical condition or state. The terms“marker” and “biomarker” are used interchangeably throughout thedisclosure. For example, the biomarkers of the present invention arecorrelated with an increased likelihood of preterm birth. Suchbiomarkers include, but are not limited to, biological moleculescomprising nucleotides, nucleic acids, nucleosides, amino acids, sugars,fatty acids, steroids, metabolites, peptides, polypeptides, proteins,carbohydrates, lipids, hormones, antibodies, regions of interest thatserve as surrogates for biological macromolecules and combinationsthereof (e.g., glycoproteins, ribonucleoproteins, lipoproteins). Theterm also encompasses portions or fragments of a biological molecule,for example, peptide fragment of a protein or polypeptide that comprisesat least 5 consecutive amino acid residues, at least 6 consecutive aminoacid residues, at least 7 consecutive amino acid residues, at least 8consecutive amino acid residues, at least 9 consecutive amino acidresidues, at least 10 consecutive amino acid residues, at least 11consecutive amino acid residues, at least 12 consecutive amino acidresidues, at least 13 consecutive amino acid residues, at least 14consecutive amino acid residues, at least 15 consecutive amino acidresidues, at least 5 consecutive amino acid residues, at least 16consecutive amino acid residues, at least 17 consecutive amino acidresidues, at least 18 consecutive amino acid residues, at least 19consecutive amino acid residues, at least 20 consecutive amino acidresidues, at least 21 consecutive amino acid residues, at least 22consecutive amino acid residues, at least 23 consecutive amino acidresidues, at least 24 consecutive amino acid residues, at least 25consecutive amino acid residues, or more consecutive amino acidresidues.

The invention also provides a method of determining probability forpreterm birth in a pregnant female, the method comprising detecting ameasurable feature of each of N biomarkers selected from the biomarkerslisted in Tables 1 through 63 in a biological sample obtained from thepregnant female, and analyzing the measurable feature to determine theprobability for preterm birth in the pregnant female. As disclosedherein, a measurable feature comprises fragments or derivatives of eachof said N biomarkers selected from the biomarkers listed in Tables 1through 63. In some embodiments of the disclosed methods detecting ameasurable feature comprises quantifying an amount of each of Nbiomarkers selected from the biomarkers listed in Tables 1 through 63,combinations or portions and/or derivatives thereof in a biologicalsample obtained from said pregnant female.

The invention further provides a method of predicting GAB, the methodencompassing detecting a measurable feature of each of N biomarkersselected from the biomarkers listed in Tables 1 through 63 in abiological sample obtained from a pregnant female, and analyzing themeasurable feature to predict GAB.

The invention also provides a method of predicting GAB, the methodcomprising: (a) quantifying in a biological sample obtained from thepregnant female an amount of each of N biomarkers selected from thebiomarkers listed in Tables 1 through 63; (b) multiplying orthresholding the amount by a predetermined coefficient, (c) determiningthe predicted GAB birth in the pregnant female comprising adding theindividual products to obtain a total risk score that corresponds to thepredicted GAB.

The invention further provides a method of predicting time to birth in apregnant female, the method comprising: (a) obtaining a biologicalsample from the pregnant female; (b) quantifying an amount of each of Nbiomarkers selected from the biomarkers listed in Tables 1 through 63 inthe biological sample; (c) multiplying or thresholding the amount by apredetermined coefficient, (d) determining predicted GAB in the pregnantfemale comprising adding the individual products to obtain a total riskscore that corresponds to the predicted GAB; and (e) subtracting theestimated gestational age (GA) at time biological sample was obtainedfrom the predicted GAB to predict time to birth in said pregnant female.For methods directed to predicting time to birth, it is understood that“birth” means birth following spontaneous onset of labor, with orwithout rupture of membranes.

Although described and exemplified with reference to methods ofdetermining probability for preterm birth in a pregnant female, thepresent disclosure is similarly applicable to the methods of predictingGAB, the methods for predicting term birth, methods for determining theprobability of term birth in a pregnant female as well methods ofpredicting time to birth in a pregnant female. It will be apparent toone skilled in the art that each of the aforementioned methods hasspecific and substantial utilities and benefits with regardmaternal-fetal health considerations.

In some embodiments, the method of determining probability for pretermbirth in a pregnant female and related methods disclosed herein comprisedetecting a measurable feature of each of N biomarkers, wherein N isselected from the group consisting of 2 to 24. In further embodiments,the disclosed methods of determining probability for preterm birth in apregnant female and related methods disclosed herein comprise detectinga measurable feature of each of at least two isolated biomarkersselected from the group consisting of AFTECCVVASQLR, ELLESYIDGR, andITLPDFTGDLR. In further embodiments, the disclosed methods ofdetermining probability for preterm birth in a pregnant female andrelated methods disclosed herein comprise detecting a measurable featureof each of at least two isolated biomarkers selected from the groupconsisting of FLNWIK, FGFGGSTDSGPIR, LLELTGPK, VEHSDLSFSK,IEGNLIFDPNNYLPK, ALVLELAK, TQILEWAAER, DVLLLVHNLPQNLPGYFWYK, SEPRPGVLLR,ITQDAQLK, ALDLSLK, WWGGQPLWITATK, and LSETNR.

In additional embodiments, the disclosed methods of determiningprobability for preterm birth in a pregnant female and related methodsdisclosed herein comprise detecting a measurable feature of each of atleast two isolated biomarkers selected from the group consisting of thebiomarkers set forth in Table 50 and the biomarkers set forth in Table52.

In additional embodiments, the method of determining probability forpreterm birth in a pregnant female and related methods disclosed hereincomprise detecting a measurable feature of each of at least two isolatedbiomarkers selected from the group consisting oflipopolysaccharide-binding protein (LBP), prothrombin (THRB), complementcomponent C5 (C5 or CO5), plasminogen (PLMN), and complement componentC8 gamma chain (C8G or CO8G).

In additional embodiments, the method of determining probability forpreterm birth in a pregnant female and related methods disclosed hereincomprise detecting a measurable feature of each of at least two isolatedbiomarkers selected from the group consisting of Alpha-1B-glycoprotein(A1BG), Disintegrin and metalloproteinase domain-containing protein 12(ADA12), Apolipoprotein B-100 (APOB), Beta-2-microglobulin (B2MG),CCAAT/enhancer-binding protein alpha/beta (HP8 Peptide),Corticosteroid-binding globulin (CBG), Complement component C6, Endoglin(EGLN), Ectonucleotide pyrophosphatase/phosphodiesterase family member 2(ENPP2), Coagulation factor VII (FA7), Hyaluronan-binding protein 2(HABP2), Pregnancy-specific beta-1-glycoprotein 9 (PSG9), Inhibin beta Echain (INHBE).

In further embodiments, the disclosed method of determining probabilityfor preterm birth in a pregnant female and related methods disclosedherein comprise detecting a measurable feature of each of at least twoisolated biomarkers selected from the group consisting oflipopolysaccharide-binding protein (LBP), prothrombin (THRB), complementcomponent C5 (C5 or CO5), plasminogen (PLMN), complement component C8gamma chain (C8G or CO8G), complement component 1, q subcomponent, Bchain (C1QB), fibrinogen beta chain (FIBB or FIB), C-reactive protein(CRP), inter-alpha-trypsin inhibitor heavy chain H4 (ITIH4), chorionicsomatomammotropin hormone (CSH), and angiotensinogen (ANG or ANGT).

In further embodiments, the disclosed method of determining probabilityfor preterm birth in a pregnant female and related methods disclosedherein comprise detecting a measurable feature of each of at least twoisolated biomarkers selected from the group consisting ofAlpha-1B-glycoprotein (A1BG), Disintegrin and metalloproteinasedomain-containing protein 12 (ADA12), Apolipoprotein B-100 (APOB),Beta-2-microglobulin (B2MG), CCAAT/enhancer-binding protein alpha/beta(HP8 Peptide), Corticosteroid-binding globulin (CBG), Complementcomponent C6, Endoglin (EGLN), Ectonucleotidepyrophosphatase/phosphodiesterase family member 2 (ENPP2), Coagulationfactor VII (FA7), Hyaluronan-binding protein 2 (HABP2),Pregnancy-specific beta-1-glycoprotein 9 (PSG9), Inhibin beta E chain(INHBE).

In further embodiments, the disclosed method of determining probabilityfor preterm birth in a pregnant female and related methods disclosedherein comprise detecting a measurable feature of each of at least twoisolated biomarkers selected from the group consisting ofAlpha-1B-glycoprotein (A1BG), Disintegrin and metalloproteinasedomain-containing protein 12 (ADA12), Apolipoprotein B-100 (APOB),Beta-2-microglobulin (B2MG), CCAAT/enhancer-binding protein alpha/beta(HP8 Peptide), Corticosteroid-binding globulin (CBG), Complementcomponent C6, Endoglin (EGLN), Ectonucleotidepyrophosphatase/phosphodiesterase family member 2 (ENPP2), Coagulationfactor VII (FA7), Hyaluronan-binding protein 2 (HABP2),Pregnancy-specific beta-1-glycoprotein 9 (PSG9), Inhibin beta E chain(INHBE).

In further embodiments, the disclosed method of determining probabilityfor preterm birth in a pregnant female and related methods disclosedherein comprise detecting a measurable feature of each of at least twoisolated biomarkers selected from the group consisting of the biomarkersset forth in Table 51 and the biomarkers set forth in Table 53.

In additional embodiments, the methods of determining probability forpreterm birth in a pregnant female further encompass detecting ameasurable feature for one or more risk indicia associated with pretermbirth. In additional embodiments the risk indicia are selected form thegroup consisting of previous low birth weight or preterm delivery,multiple 2nd trimester spontaneous abortions, prior first trimesterinduced abortion, familial and intergenerational factors, history ofinfertility, nulliparity, placental abnormalities, cervical and uterineanomalies, gestational bleeding, intrauterine growth restriction, inutero diethylstilbestrol exposure, multiple gestations, infant sex,short stature, low prepregnancy weight, low or high body mass index,diabetes, hypertension, and urogenital infections.

A “measurable feature” is any property, characteristic or aspect thatcan be determined and correlated with the probability for preterm birthin a subject. The term further encompasses any property, characteristicor aspect that can be determined and correlated in connection with aprediction of GAB, a prediction of term birth, or a prediction of timeto birth in a pregnant female. For a biomarker, such a measurablefeature can include, for example, the presence, absence, orconcentration of the biomarker, or a fragment thereof, in the biologicalsample, an altered structure, such as, for example, the presence oramount of a post-translational modification, such as oxidation at one ormore positions on the amino acid sequence of the biomarker or, forexample, the presence of an altered conformation in comparison to theconformation of the biomarker in normal control subjects, and/or thepresence, amount, or altered structure of the biomarker as a part of aprofile of more than one biomarker. In addition to biomarkers,measurable features can further include risk indicia including, forexample, maternal characteristics, age, race, ethnicity, medicalhistory, past pregnancy history, obstetrical history. For a riskindicium, a measurable feature can include, for example, previous lowbirth weight or preterm delivery, multiple 2nd trimester spontaneousabortions, prior first trimester induced abortion, familial andintergenerational factors, history of infertility, nulliparity,placental abnormalities, cervical and uterine anomalies, short cervicallength measurements, gestational bleeding, intrauterine growthrestriction, in utero diethylstilbestrol exposure, multiple gestations,infant sex, short stature, low prepregnancy weight/low body mass index,diabetes, hypertension, urogenital infections, hypothyroidism, asthma,low educational attainment, cigarette smoking, drug use and alcoholconsumption.

In some embodiments of the disclosed methods of determining probabilityfor preterm birth in a pregnant female, the probability for pretermbirth in the pregnant female is calculated based on the quantifiedamount of each of N biomarkers selected from the biomarkers listed inTables 1 through 63. In some embodiments, the disclosed methods fordetermining the probability of preterm birth encompass detecting and/orquantifying one or more biomarkers using mass spectrometry, a captureagent or a combination thereof.

In some embodiments, the disclosed methods of determining probabilityfor preterm birth in a pregnant female encompass an initial step ofproviding a biomarker panel comprising N of the biomarkers listed inTables 1 through 63. In additional embodiments, the disclosed methods ofdetermining probability for preterm birth in a pregnant female encompassan initial step of providing a biological sample from the pregnantfemale.

In some embodiments, the disclosed methods of determining probabilityfor preterm birth in a pregnant female encompass communicating theprobability to a health care provider. The disclosed of predicting GAB,the methods for predicting term birth, methods for determining theprobability of term birth in a pregnant female as well methods ofpredicting time to birth in a pregnant female similarly encompasscommunicating the probability to a health care provider. As statedabove, although described and exemplified with reference to determiningprobability for preterm birth in a pregnant female, all embodimentsdescribed throughout this disclosure are similarly applicable to themethods of predicting GAB, the methods for predicting term birth,methods for determining the probability of term birth in a pregnantfemale as well methods of predicting time to birth in a pregnant female.Specifically, the biomarkers and panels recited throughout thisapplication with express reference to methods for preterm birth can alsobe used in methods for predicting GAB, the methods for predicting termbirth, methods for determining the probability of term birth in apregnant female as well methods of predicting time to birth in apregnant female. It will be apparent to one skilled in the art that eachof the aforementioned methods have specific and substantial utilitiesand benefits with regard maternal-fetal health considerations.

In additional embodiments, the communication informs a subsequenttreatment decision for the pregnant female. In some embodiments, themethod of determining probability for preterm birth in a pregnant femaleencompasses the additional feature of expressing the probability as arisk score.

As used herein, the term “risk score” refers to a score that can beassigned based on comparing the amount of one or more biomarkers in abiological sample obtained from a pregnant female to a standard orreference score that represents an average amount of the one or morebiomarkers calculated from biological samples obtained from a randompool of pregnant females. Because the level of a biomarker may not bestatic throughout pregnancy, a standard or reference score has to havebeen obtained for the gestational time point that corresponds to that ofthe pregnant female at the time the sample was taken. The standard orreference score can be predetermined and built into a predictor modelsuch that the comparison is indirect rather than actually performedevery time the probability is determined for a subject. A risk score canbe a standard (e.g., a number) or a threshold (e.g., a line on a graph).The value of the risk score correlates to the deviation, upwards ordownwards, from the average amount of the one or more biomarkerscalculated from biological samples obtained from a random pool ofpregnant females. In certain embodiments, if a risk score is greaterthan a standard or reference risk score, the pregnant female can have anincreased likelihood of preterm birth. In some embodiments, themagnitude of a pregnant female's risk score, or the amount by which itexceeds a reference risk score, can be indicative of or correlated tothat pregnant female's level of risk.

In the context of the present invention, the term “biological sample,”encompasses any sample that is taken from pregnant female and containsone or more of the biomarkers listed in Tables 1 through 63. Suitablesamples in the context of the present invention include, for example,blood, plasma, serum, amniotic fluid, vaginal secretions, saliva, andurine. In some embodiments, the biological sample is selected from thegroup consisting of whole blood, plasma, and serum. In a particularembodiment, the biological sample is serum. As will be appreciated bythose skilled in the art, a biological sample can include any fractionor component of blood, without limitation, T cells, monocytes,neutrophils, erythrocytes, platelets and microvesicles such as exosomesand exosome-like vesicles. In a particular embodiment, the biologicalsample is serum.

Preterm birth refers to delivery or birth at a gestational age less than37 completed weeks. Other commonly used subcategories of preterm birthhave been established and delineate moderately preterm (birth at 33 to36 weeks of gestation), very preterm (birth at <33 weeks of gestation),and extremely preterm (birth at ≤28 weeks of gestation). With regard tothe methods disclosed herein, those skilled in the art understand thatthe cut-offs that delineate preterm birth and term birth as well as thecut-offs that delineate subcategories of preterm birth can be adjustedin practicing the methods disclosed herein, for example, to maximize aparticular health benefit. It is further understood that suchadjustments are well within the skill set of individuals consideredskilled in the art and encompassed within the scope of the inventionsdisclosed herein. Gestational age is a proxy for the extent of fetaldevelopment and the fetus's readiness for birth. Gestational age hastypically been defined as the length of time from the date of the lastnormal menses to the date of birth. However, obstetric measures andultrasound estimates also can aid in estimating gestational age. Pretermbirths have generally been classified into two separate subgroups. One,spontaneous preterm births are those occurring subsequent to spontaneousonset of preterm labor or preterm premature rupture of membranesregardless of subsequent labor augmentation or cesarean delivery. Two,indicated preterm births are those occurring following induction orcesarean section for one or more conditions that the woman's caregiverdetermines to threaten the health or life of the mother and/or fetus. Insome embodiments, the methods disclosed herein are directed todetermining the probability for spontaneous preterm birth. In additionalembodiments, the methods disclosed herein are directed to predictinggestational birth.

As used herein, the term “estimated gestational age” or “estimated GA”refers to the GA determined based on the date of the last normal mensesand additional obstetric measures, ultrasound estimates or otherclinical parameters including, without limitation, those described inthe preceding paragraph. In contrast the term “predicted gestational ageat birth” or “predicted GAB” refers to the GAB determined based on themethods of the invention as disclosed herein. As used herein, “termbirth” refers to birth at a gestational age equal or more than 37completed weeks.

In some embodiments, the pregnant female is between 17 and 28 weeks ofgestation at the time the biological sample is collected. In otherembodiments, the pregnant female is between 16 and 29 weeks, between 17and 28 weeks, between 18 and 27 weeks, between 19 and 26 weeks, between20 and 25 weeks, between 21 and 24 weeks, or between 22 and 23 weeks ofgestation at the time the biological sample is collected. In furtherembodiments, the pregnant female is between about 17 and 22 weeks,between about 16 and 22 weeks between about 22 and 25 weeks, betweenabout 13 and 25 weeks, between about 26 and 28, or between about 26 and29 weeks of gestation at the time the biological sample is collected.Accordingly, the gestational age of a pregnant female at the time thebiological sample is collected can be 15, 16, 17, 18, 19, 20, 21, 22,23, 24, 25, 26, 27, 28, 29 or 30 weeks.

In some embodiments of the claimed methods the measurable featurecomprises fragments or derivatives of each of the N biomarkers selectedfrom the biomarkers listed in Tables 1 through 63. In additionalembodiments of the claimed methods, detecting a measurable featurecomprises quantifying an amount of each of N biomarkers selected fromthe biomarkers listed in Tables 1 through 63, combinations or portionsand/or derivatives thereof in a biological sample obtained from saidpregnant female.

The term “amount” or “level” as used herein refers to a quantity of abiomarker that is detectable or measurable in a biological sample and/orcontrol. The quantity of a biomarker can be, for example, a quantity ofpolypeptide, the quantity of nucleic acid, or the quantity of a fragmentor surrogate. The term can alternatively include combinations thereof.The term “amount” or “level” of a biomarker is a measurable feature ofthat biomarker.

In some embodiments, calculating the probability for preterm birth in apregnant female is based on the quantified amount of each of Nbiomarkers selected from the biomarkers listed in Tables 1 through 63.Any existing, available or conventional separation, detection andquantification methods can be used herein to measure the presence orabsence (e.g., readout being present vs. absent; or detectable amountvs. undetectable amount) and/or quantity (e.g., readout being anabsolute or relative quantity, such as, for example, absolute orrelative concentration) of biomarkers, peptides, polypeptides, proteinsand/or fragments thereof and optionally of the one or more otherbiomarkers or fragments thereof in samples. In some embodiments,detection and/or quantification of one or more biomarkers comprises anassay that utilizes a capture agent. In further embodiments, the captureagent is an antibody, antibody fragment, nucleic acid-based proteinbinding reagent, small molecule or variant thereof. In additionalembodiments, the assay is an enzyme immunoassay (EIA), enzyme-linkedimmunosorbent assay (ELISA), and radioimmunoassay (MA). In someembodiments, detection and/or quantification of one or more biomarkersfurther comprises mass spectrometry (MS). In yet further embodiments,the mass spectrometry is co-immunoprecipitation-mass spectrometry (co-IPMS), where coimmunoprecipitation, a technique suitable for the isolationof whole protein complexes is followed by mass spectrometric analysis.

As used herein, the term “mass spectrometer” refers to a device able tovolatilize/ionize analytes to form gas-phase ions and determine theirabsolute or relative molecular masses. Suitable methods ofvolatilization/ionization are matrix-assisted laser desorptionionization (MALDI), electrospray, laser/light, thermal, electrical,atomized/sprayed and the like, or combinations thereof. Suitable formsof mass spectrometry include, but are not limited to, ion trapinstruments, quadrupole instruments, electrostatic and magnetic sectorinstruments, time of flight instruments, time of flight tandem massspectrometer (TOF MS/MS), Fourier-transform mass spectrometers,Orbitraps and hybrid instruments composed of various combinations ofthese types of mass analyzers. These instruments can, in turn, beinterfaced with a variety of other instruments that fractionate thesamples (for example, liquid chromatography or solid-phase adsorptiontechniques based on chemical, or biological properties) and that ionizethe samples for introduction into the mass spectrometer, includingmatrix-assisted laser desorption (MALDI), electrospray, or nanosprayionization (ESI) or combinations thereof.

Generally, any mass spectrometric (MS) technique that can provideprecise information on the mass of peptides, and preferably also onfragmentation and/or (partial) amino acid sequence of selected peptides(e.g., in tandem mass spectrometry, MS/MS; or in post source decay, TOFMS), can be used in the methods disclosed herein. Suitable peptide MSand MS/MS techniques and systems are well-known per se (see, e.g.,Methods in Molecular Biology, vol. 146: “Mass Spectrometry of Proteinsand Peptides”, by Chapman, ed., Humana Press 2000; Biemann 1990. MethodsEnzymol 193: 455-79; or Methods in Enzymology, vol. 402: “BiologicalMass Spectrometry”, by Burlingame, ed., Academic Press 2005) and can beused in practicing the methods disclosed herein. Accordingly, in someembodiments, the disclosed methods comprise performing quantitative MSto measure one or more biomarkers. Such quantitative methods can beperformed in an automated (Villanueva, et al., Nature Protocols (2006)1(2):880-891) or semi-automated format. In particular embodiments, MScan be operably linked to a liquid chromatography device (LC-MS/MS orLC-MS) or gas chromatography device (GC-MS or GC-MS/MS). Other methodsuseful in this context include isotope-coded affinity tag (ICAT), tandemmass tags (TMT), or stable isotope labeling by amino acids in cellculture (SILAC), followed by chromatography and MS/MS.

As used herein, the terms “multiple reaction monitoring (MRM)” or“selected reaction monitoring (SRM)” refer to an MS-based quantificationmethod that is particularly useful for quantifying analytes that are inlow abundance. In an SRM experiment, a predefined precursor ion and oneor more of its fragments are selected by the two mass filters of atriple quadrupole instrument and monitored over time for precisequantification. Multiple SRM precursor and fragment ion pairs can bemeasured within the same experiment on the chromatographic time scale byrapidly toggling between the different precursor/fragment pairs toperform an MRM experiment. A series of transitions (precursor/fragmention pairs) in combination with the retention time of the targetedanalyte (e.g., peptide or small molecule such as chemical entity,steroid, hormone) can constitute a definitive assay. A large number ofanalytes can be quantified during a single LC-MS experiment. The term“scheduled,” or “dynamic” in reference to MRM or SRM, refers to avariation of the assay wherein the transitions for a particular analyteare only acquired in a time window around the expected retention time,significantly increasing the number of analytes that can be detected andquantified in a single LC-MS experiment and contributing to theselectivity of the test, as retention time is a property dependent onthe physical nature of the analyte. A single analyte can also bemonitored with more than one transition. Finally, included in the assaycan be standards that correspond to the analytes of interest (e.g., sameamino acid sequence), but differ by the inclusion of stable isotopes.Stable isotopic standards (SIS) can be incorporated into the assay atprecise levels and used to quantify the corresponding unknown analyte.An additional level of specificity is contributed by the co-elution ofthe unknown analyte and its corresponding SIS and properties of theirtransitions (e.g., the similarity in the ratio of the level of twotransitions of the unknown and the ratio of the two transitions of itscorresponding SIS).

Mass spectrometry assays, instruments and systems suitable for biomarkerpeptide analysis can include, without limitation, matrix-assisted laserdesorption/ionisation time-of-flight (MALDI-TOF) MS; MALDI-TOFpost-source-decay (PSD); MALDI-TOF/TOF; surface-enhanced laserdesorption/ionization time-of-flight mass spectrometry (SELDI-TOF) MS;electrospray ionization mass spectrometry (ESI-MS); ESI-MS/MS;ESI-MS/(MS)_(n) (n is an integer greater than zero); ESI 3D or linear(2D) ion trap MS; ESI triple quadrupole MS; ESI quadrupole orthogonalTOF (Q-TOF); ESI Fourier transform MS systems; desorption/ionization onsilicon (DIOS); secondary ion mass spectrometry (SIMS); atmosphericpressure chemical ionization mass spectrometry (APCI-MS); APCI-MS/MS;APCI-(MS)_(n); ion mobility spectrometry (IMS); inductively coupledplasma mass spectrometry (ICP-MS) atmospheric pressure photoionizationmass spectrometry (APPI-MS); APPI-MS/MS; and APPI-(MS)_(n). Peptide ionfragmentation in tandem MS (MS/MS) arrangements can be achieved usingmanners established in the art, such as, e.g., collision induceddissociation (CID). As described herein, detection and quantification ofbiomarkers by mass spectrometry can involve multiple reaction monitoring(MRM), such as described among others by Kuhn et al. Proteomics 4:1175-86 (2004). Scheduled multiple-reaction-monitoring (Scheduled MRM)mode acquisition during LC-MS/MS analysis enhances the sensitivity andaccuracy of peptide quantitation. Anderson and Hunter, Molecular andCellular Proteomics 5(4):573 (2006). As described herein, massspectrometry-based assays can be advantageously combined with upstreampeptide or protein separation or fractionation methods, such as forexample with the chromatographic and other methods described hereinbelow. As further described herein, shotgun quantitative proteomics canbe combined with SRM/MRM-based assays for high-throughput identificationand verification of prognostic biomarkers of preterm birth.

A person skilled in the art will appreciate that a number of methods canbe used to determine the amount of a biomarker, including massspectrometry approaches, such as MS/MS, LC-MS/MS, multiple reactionmonitoring (MRM) or SRM and product-ion monitoring (PIM) and alsoincluding antibody based methods such as immunoassays such as Westernblots, enzyme-linked immunosorbant assay (ELISA), immunoprecipitation,immunohistochemistry, immunofluorescence, radioimmunoassay, dotblotting, and FACS. Accordingly, in some embodiments, determining thelevel of the at least one biomarker comprises using an immunoassayand/or mass spectrometric methods. In additional embodiments, the massspectrometric methods are selected from MS, MS/MS, LC-MS/MS, SRM, PIM,and other such methods that are known in the art. In other embodiments,LC-MS/MS further comprises 1D LC-MS/MS, 2D LC-MS/MS or 3D LC-MS/MS.Immunoassay techniques and protocols are generally known to thoseskilled in the art (Price and Newman, Principles and Practice ofImmunoassay, 2nd Edition, Grove's Dictionaries, 1997; and Gosling,Immunoassays: A Practical Approach, Oxford University Press, 2000.) Avariety of immunoassay techniques, including competitive andnon-competitive immunoassays, can be used (Self et al., Curr. Opin.Biotechnol., 7:60-65 (1996).

In further embodiments, the immunoassay is selected from Western blot,ELISA, immunoprecipitation, immunohistochemistry, immunofluorescence,radioimmunoassay (MA), dot blotting, and FACS. In certain embodiments,the immunoassay is an ELISA. In yet a further embodiment, the ELISA isdirect ELISA (enzyme-linked immunosorbent assay), indirect ELISA,sandwich ELISA, competitive ELISA, multiplex ELISA, ELISPOTtechnologies, and other similar techniques known in the art. Principlesof these immunoassay methods are known in the art, for example John R.Crowther, The ELISA Guidebook, 1st ed., Humana Press 2000, ISBN0896037282. Typically ELISAs are performed with antibodies but they canbe performed with any capture agents that bind specifically to one ormore biomarkers of the invention and that can be detected. MultiplexELISA allows simultaneous detection of two or more analytes within asingle compartment (e.g., microplate well) usually at a plurality ofarray addresses (Nielsen and Geierstanger 2004. J Immunol Methods 290:107-20 (2004) and Ling et al. 2007. Expert Rev Mol Diagn 7: 87-98(2007)).

In some embodiments, Radioimmunoassay (RIA) can be used to detect one ormore biomarkers in the methods of the invention. RIA is acompetition-based assay that is well known in the art and involvesmixing known quantities of radioactively-labelled (e.g., ¹²⁵I or¹³¹I-labelled) target analyte with antibody specific for the analyte,then adding non-labelled analyte from a sample and measuring the amountof labelled analyte that is displaced (see, e.g., An Introduction toRadioimmunoassay and Related Techniques, by Chard T, ed., ElsevierScience 1995, ISBN 0444821198 for guidance).

A detectable label can be used in the assays described herein for director indirect detection of the biomarkers in the methods of the invention.A wide variety of detectable labels can be used, with the choice oflabel depending on the sensitivity required, ease of conjugation withthe antibody, stability requirements, and available instrumentation anddisposal provisions. Those skilled in the art are familiar withselection of a suitable detectable label based on the assay detection ofthe biomarkers in the methods of the invention. Suitable detectablelabels include, but are not limited to, fluorescent dyes (e.g.,fluorescein, fluorescein isothiocyanate (FITC), Oregon Green™,rhodamine, Texas red, tetrarhodimine isothiocynate (TRITC), Cy3, Cy5,etc.), fluorescent markers (e.g., green fluorescent protein (GFP),phycoerythrin, etc.), enzymes (e.g., luciferase, horseradish peroxidase,alkaline phosphatase, etc.), nanoparticles, biotin, digoxigenin, metals,and the like.

For mass-spectrometry based analysis, differential tagging with isotopicreagents, e.g., isotope-coded affinity tags (ICAT) or the more recentvariation that uses isobaric tagging reagents, iTRAQ (AppliedBiosystems, Foster City, Calif.), or tandem mass tags, TMT, (ThermoScientific, Rockford, Ill.), followed by multidimensional liquidchromatography (LC) and tandem mass spectrometry (MS/MS) analysis canprovide a further methodology in practicing the methods of theinvention.

A chemiluminescence assay using a chemiluminescent antibody can be usedfor sensitive, non-radioactive detection of protein levels. An antibodylabeled with fluorochrome also can be suitable. Examples offluorochromes include, without limitation, DAPI, fluorescein, Hoechst33258, R-phycocyanin, B-phycoerythrin, R-phycoerythrin, rhodamine, Texasred, and lissamine. Indirect labels include various enzymes well knownin the art, such as horseradish peroxidase (HRP), alkaline phosphatase(AP), beta-galactosidase, urease, and the like. Detection systems usingsuitable substrates for horseradish-peroxidase, alkaline phosphatase,beta-galactosidase are well known in the art.

A signal from the direct or indirect label can be analyzed, for example,using a spectrophotometer to detect color from a chromogenic substrate;a radiation counter to detect radiation such as a gamma counter fordetection of ¹²⁵I; or a fluorometer to detect fluorescence in thepresence of light of a certain wavelength. For detection ofenzyme-linked antibodies, a quantitative analysis can be made using aspectrophotometer such as an EMAX Microplate Reader (Molecular Devices;Menlo Park, Calif.) in accordance with the manufacturer's instructions.If desired, assays used to practice the invention can be automated orperformed robotically, and the signal from multiple samples can bedetected simultaneously.

In some embodiments, the methods described herein encompassquantification of the biomarkers using mass spectrometry (MS). Infurther embodiments, the mass spectrometry can be liquidchromatography-mass spectrometry (LC-MS), multiple reaction monitoring(MRM) or selected reaction monitoring (SRM). In additional embodiments,the MRM or SRM can further encompass scheduled MRM or scheduled SRM.

As described above, chromatography can also be used in practicing themethods of the invention. Chromatography encompasses methods forseparating chemical substances and generally involves a process in whicha mixture of analytes is carried by a moving stream of liquid or gas(“mobile phase”) and separated into components as a result ofdifferential distribution of the analytes as they flow around or over astationary liquid or solid phase (“stationary phase”), between themobile phase and said stationary phase. The stationary phase can beusually a finely divided solid, a sheet of filter material, or a thinfilm of a liquid on the surface of a solid, or the like. Chromatographyis well understood by those skilled in the art as a technique applicablefor the separation of chemical compounds of biological origin, such as,e.g., amino acids, proteins, fragments of proteins or peptides, etc.

Chromatography can be columnar (i.e., wherein the stationary phase isdeposited or packed in a column), preferably liquid chromatography, andyet more preferably high-performance liquid chromatography (HPLC), orultra high performance/pressure liquid chromatography (UHPLC).Particulars of chromatography are well known in the art (Bidlingmeyer,Practical HPLC Methodology and Applications, John Wiley & Sons Inc.,1993). Exemplary types of chromatography include, without limitation,high-performance liquid chromatography (HPLC), UHPLC, normal phase HPLC(NP-HPLC), reversed phase HPLC (RP-HPLC), ion exchange chromatography(IEC), such as cation or anion exchange chromatography, hydrophilicinteraction chromatography (HILIC), hydrophobic interactionchromatography (HIC), size exclusion chromatography (SEC) including gelfiltration chromatography or gel permeation chromatography,chromatofocusing, affinity chromatography such as immuno-affinity,immobilised metal affinity chromatography, and the like. Chromatography,including single-, two- or more-dimensional chromatography, can be usedas a peptide fractionation method in conjunction with a further peptideanalysis method, such as for example, with a downstream massspectrometry analysis as described elsewhere in this specification.

Further peptide or polypeptide separation, identification orquantification methods can be used, optionally in conjunction with anyof the above described analysis methods, for measuring biomarkers in thepresent disclosure. Such methods include, without limitation, chemicalextraction partitioning, isoelectric focusing (IEF) including capillaryisoelectric focusing (CIEF), capillary isotachophoresis (CITP),capillary electrochromatography (CEC), and the like, one-dimensionalpolyacrylamide gel electrophoresis (PAGE), two-dimensionalpolyacrylamide gel electrophoresis (2D-PAGE), capillary gelelectrophoresis (CGE), capillary zone electrophoresis (CZE), micellarelectrokinetic chromatography (MEKC), free flow electrophoresis (FFE),etc.

In the context of the invention, the term “capture agent” refers to acompound that can specifically bind to a target, in particular abiomarker. The term includes antibodies, antibody fragments, nucleicacid-based protein binding reagents (e.g. aptamers, Slow Off-rateModified Aptamers (SOMAmer™)), protein-capture agents, natural ligands(i.e. a hormone for its receptor or vice versa), small molecules orvariants thereof.

Capture agents can be configured to specifically bind to a target, inparticular a biomarker. Capture agents can include but are not limitedto organic molecules, such as polypeptides, polynucleotides and othernon polymeric molecules that are identifiable to a skilled person. Inthe embodiments disclosed herein, capture agents include any agent thatcan be used to detect, purify, isolate, or enrich a target, inparticular a biomarker. Any art-known affinity capture technologies canbe used to selectively isolate and enrich/concentrate biomarkers thatare components of complex mixtures of biological media for use in thedisclosed methods.

Antibody capture agents that specifically bind to a biomarker can beprepared using any suitable methods known in the art. See, e.g.,Coligan, Current Protocols in Immunology (1991); Harlow & Lane,Antibodies: A Laboratory Manual (1988); Goding, Monoclonal Antibodies:Principles and Practice (2d ed. 1986). Antibody capture agents can beany immunoglobulin or derivative thereof, whether natural or wholly orpartially synthetically produced. All derivatives thereof which maintainspecific binding ability are also included in the term. Antibody captureagents have a binding domain that is homologous or largely homologous toan immunoglobulin binding domain and can be derived from naturalsources, or partly or wholly synthetically produced. Antibody captureagents can be monoclonal or polyclonal antibodies. In some embodiments,an antibody is a single chain antibody. Those of ordinary skill in theart will appreciate that antibodies can be provided in any of a varietyof forms including, for example, humanized, partially humanized,chimeric, chimeric humanized, etc. Antibody capture agents can beantibody fragments including, but not limited to, Fab, Fab′, F(ab′)2,scFv, Fv, dsFv diabody, and Fd fragments. An antibody capture agent canbe produced by any means. For example, an antibody capture agent can beenzymatically or chemically produced by fragmentation of an intactantibody and/or it can be recombinantly produced from a gene encodingthe partial antibody sequence. An antibody capture agent can comprise asingle chain antibody fragment. Alternatively or additionally, antibodycapture agent can comprise multiple chains which are linked together,for example, by disulfide linkages; and, any functional fragmentsobtained from such molecules, wherein such fragments retainspecific-binding properties of the parent antibody molecule. Because oftheir smaller size as functional components of the whole molecule,antibody fragments can offer advantages over intact antibodies for usein certain immunochemical techniques and experimental applications.

Suitable capture agents useful for practicing the invention also includeaptamers. Aptamers are oligonucleotide sequences that can bind to theirtargets specifically via unique three dimensional (3-D) structures. Anaptamer can include any suitable number of nucleotides and differentaptamers can have either the same or different numbers of nucleotides.Aptamers can be DNA or RNA or chemically modified nucleic acids and canbe single stranded, double stranded, or contain double stranded regions,and can include higher ordered structures. An aptamer can also be aphotoaptamer, where a photoreactive or chemically reactive functionalgroup is included in the aptamer to allow it to be covalently linked toits corresponding target. Use of an aptamer capture agent can includethe use of two or more aptamers that specifically bind the samebiomarker. An aptamer can include a tag. An aptamer can be identifiedusing any known method, including the SELEX (systematic evolution ofligands by exponential enrichment), process. Once identified, an aptamercan be prepared or synthesized in accordance with any known method,including chemical synthetic methods and enzymatic synthetic methods andused in a variety of applications for biomarker detection. Liu et al.,Curr Med Chem. 18(27):4117-25 (2011). Capture agents useful inpracticing the methods of the invention also include SOMAmers (SlowOff-Rate Modified Aptamers) known in the art to have improved off-ratecharacteristics. Brody et al., J Mol Biol. 422(5):595-606 (2012).SOMAmers can be generated using any known method, including the SELEXmethod.

It is understood by those skilled in the art that biomarkers can bemodified prior to analysis to improve their resolution or to determinetheir identity. For example, the biomarkers can be subject toproteolytic digestion before analysis. Any protease can be used.Proteases, such as trypsin, that are likely to cleave the biomarkersinto a discrete number of fragments are particularly useful. Thefragments that result from digestion function as a fingerprint for thebiomarkers, thereby enabling their detection indirectly. This isparticularly useful where there are biomarkers with similar molecularmasses that might be confused for the biomarker in question. Also,proteolytic fragmentation is useful for high molecular weight biomarkersbecause smaller biomarkers are more easily resolved by massspectrometry. In another example, biomarkers can be modified to improvedetection resolution. For instance, neuraminidase can be used to removeterminal sialic acid residues from glycoproteins to improve binding toan anionic adsorbent and to improve detection resolution. In anotherexample, the biomarkers can be modified by the attachment of a tag ofparticular molecular weight that specifically binds to molecularbiomarkers, further distinguishing them. Optionally, after detectingsuch modified biomarkers, the identity of the biomarkers can be furtherdetermined by matching the physical and chemical characteristics of themodified biomarkers in a protein database (e.g., SwissProt).

It is further appreciated in the art that biomarkers in a sample can becaptured on a substrate for detection. Traditional substrates includeantibody-coated 96-well plates or nitrocellulose membranes that aresubsequently probed for the presence of the proteins. Alternatively,protein-binding molecules attached to microspheres, microparticles,microbeads, beads, or other particles can be used for capture anddetection of biomarkers. The protein-binding molecules can beantibodies, peptides, peptoids, aptamers, small molecule ligands orother protein-binding capture agents attached to the surface ofparticles. Each protein-binding molecule can include unique detectablelabel that is coded such that it can be distinguished from otherdetectable labels attached to other protein-binding molecules to allowdetection of biomarkers in multiplex assays. Examples include, but arenot limited to, color-coded microspheres with known fluorescent lightintensities (see e.g., microspheres with xMAP technology produced byLuminex (Austin, Tex.); microspheres containing quantum dotnanocrystals, for example, having different ratios and combinations ofquantum dot colors (e.g., Qdot nanocrystals produced by LifeTechnologies (Carlsbad, Calif.); glass coated metal nanoparticles (seee.g., SERS nanotags produced by Nanoplex Technologies, Inc. (MountainView, Calif.); barcode materials (see e.g., sub-micron sized stripedmetallic rods such as Nanobarcodes produced by Nanoplex Technologies,Inc.), encoded microparticles with colored bar codes (see e.g., CellCardproduced by Vitra Bioscience, vitrabio.com), glass microparticles withdigital holographic code images (see e.g., CyVera microbeads produced byIllumina (San Diego, Calif.); chemiluminescent dyes, combinations of dyecompounds; and beads of detectably different sizes.

In another aspect, biochips can be used for capture and detection of thebiomarkers of the invention. Many protein biochips are known in the art.These include, for example, protein biochips produced by PackardBioScience Company (Meriden Conn.), Zyomyx (Hayward, Calif.) and Phylos(Lexington, Mass.). In general, protein biochips comprise a substratehaving a surface. A capture reagent or adsorbent is attached to thesurface of the substrate. Frequently, the surface comprises a pluralityof addressable locations, each of which location has the capture agentbound there. The capture agent can be a biological molecule, such as apolypeptide or a nucleic acid, which captures other biomarkers in aspecific manner. Alternatively, the capture agent can be achromatographic material, such as an anion exchange material or ahydrophilic material. Examples of protein biochips are well known in theart.

Measuring mRNA in a biological sample can be used as a surrogate fordetection of the level of the corresponding protein biomarker in abiological sample. Thus, any of the biomarkers or biomarker panelsdescribed herein can also be detected by detecting the appropriate RNA.Levels of mRNA can measured by reverse transcription quantitativepolymerase chain reaction (RT-PCR followed with qPCR). RT-PCR is used tocreate a cDNA from the mRNA. The cDNA can be used in a qPCR assay toproduce fluorescence as the DNA amplification process progresses. Bycomparison to a standard curve, qPCR can produce an absolute measurementsuch as number of copies of mRNA per cell. Northern blots, microarrays,Invader assays, and RT-PCR combined with capillary electrophoresis haveall been used to measure expression levels of mRNA in a sample. See GeneExpression Profiling: Methods and Protocols, Richard A. Shimkets,editor, Humana Press, 2004.

Some embodiments disclosed herein relate to diagnostic and prognosticmethods of determining the probability for preterm birth in a pregnantfemale. The detection of the level of expression of one or morebiomarkers and/or the determination of a ratio of biomarkers can be usedto determine the probability for preterm birth in a pregnant female.Such detection methods can be used, for example, for early diagnosis ofthe condition, to determine whether a subject is predisposed to pretermbirth, to monitor the progress of preterm birth or the progress oftreatment protocols, to assess the severity of preterm birth, toforecast the outcome of preterm birth and/or prospects of recovery orbirth at full term, or to aid in the determination of a suitabletreatment for preterm birth.

The quantitation of biomarkers in a biological sample can be determined,without limitation, by the methods described above as well as any othermethod known in the art. The quantitative data thus obtained is thensubjected to an analytic classification process. In such a process, theraw data is manipulated according to an algorithm, where the algorithmhas been pre-defined by a training set of data, for example as describedin the examples provided herein. An algorithm can utilize the trainingset of data provided herein, or can utilize the guidelines providedherein to generate an algorithm with a different set of data.

In some embodiments, analyzing a measurable feature to determine theprobability for preterm birth in a pregnant female encompasses the useof a predictive model. In further embodiments, analyzing a measurablefeature to determine the probability for preterm birth in a pregnantfemale encompasses comparing said measurable feature with a referencefeature. As those skilled in the art can appreciate, such comparison canbe a direct comparison to the reference feature or an indirectcomparison where the reference feature has been incorporated into thepredictive model. In further embodiments, analyzing a measurable featureto determine the probability for preterm birth in a pregnant femaleencompasses one or more of a linear discriminant analysis model, asupport vector machine classification algorithm, a recursive featureelimination model, a prediction analysis of microarray model, a logisticregression model, a CART algorithm, a flex tree algorithm, a LARTalgorithm, a random forest algorithm, a MART algorithm, a machinelearning algorithm, a penalized regression method, or a combinationthereof. In particular embodiments, the analysis comprises logisticregression.

An analytic classification process can use any one of a variety ofstatistical analytic methods to manipulate the quantitative data andprovide for classification of the sample. Examples of useful methodsinclude linear discriminant analysis, recursive feature elimination, aprediction analysis of microarray, a logistic regression, a CARTalgorithm, a FlexTree algorithm, a LART algorithm, a random forestalgorithm, a MART algorithm, machine learning algorithms; etc.

For creation of a random forest for prediction of GAB one skilled in theart can consider a set of k subjects (pregnant women) for whom thegestational age at birth (GAB) is known, and for whom N analytes(transitions) have been measured in a blood specimen taken several weeksprior to birth. A regression tree begins with a root node that containsall the subjects. The average GAB for all subjects can be calculated inthe root node. The variance of the GAB within the root node will behigh, because there is a mixture of women with different GAB's. The rootnode is then divided (partitioned) into two branches, so that eachbranch contains women with a similar GAB. The average GAB for subjectsin each branch is again calculated. The variance of the GAB within eachbranch will be lower than in the root node, because the subset of womenwithin each branch has relatively more similar GAB's than those in theroot node. The two branches are created by selecting an analyte and athreshold value for the analyte that creates branches with similar GAB.The analyte and threshold value are chosen from among the set of allanalytes and threshold values, usually with a random subset of theanalytes at each node. The procedure continues recursively producingbranches to create leaves (terminal nodes) in which the subjects havevery similar GAB's. The predicted GAB in each terminal node is theaverage GAB for subjects in that terminal node. This procedure creates asingle regression tree. A random forest can consist of several hundredor several thousand such trees.

Classification can be made according to predictive modeling methods thatset a threshold for determining the probability that a sample belongs toa given class. The probability preferably is at least 50%, or at least60%, or at least 70%, or at least 80% or higher. Classifications alsocan be made by determining whether a comparison between an obtaineddataset and a reference dataset yields a statistically significantdifference. If so, then the sample from which the dataset was obtainedis classified as not belonging to the reference dataset class.Conversely, if such a comparison is not statistically significantlydifferent from the reference dataset, then the sample from which thedataset was obtained is classified as belonging to the reference datasetclass.

The predictive ability of a model can be evaluated according to itsability to provide a quality metric, e.g. AUROC (area under the ROCcurve) or accuracy, of a particular value, or range of values. Areaunder the curve measures are useful for comparing the accuracy of aclassifier across the complete data range. Classifiers with a greaterAUC have a greater capacity to classify unknowns correctly between twogroups of interest. In some embodiments, a desired quality threshold isa predictive model that will classify a sample with an accuracy of atleast about 0.5, at least about 0.55, at least about 0.6, at least about0.7, at least about 0.75, at least about 0.8, at least about 0.85, atleast about 0.9, at least about 0.95, or higher. As an alternativemeasure, a desired quality threshold can refer to a predictive modelthat will classify a sample with an AUC of at least about 0.7, at leastabout 0.75, at least about 0.8, at least about 0.85, at least about 0.9,or higher.

As is known in the art, the relative sensitivity and specificity of apredictive model can be adjusted to favor either the selectivity metricor the sensitivity metric, where the two metrics have an inverserelationship. The limits in a model as described above can be adjustedto provide a selected sensitivity or specificity level, depending on theparticular requirements of the test being performed. One or both ofsensitivity and specificity can be at least about 0.7, at least about0.75, at least about 0.8, at least about 0.85, at least about 0.9, orhigher.

The raw data can be initially analyzed by measuring the values for eachbiomarker, usually in triplicate or in multiple triplicates. The datacan be manipulated, for example, raw data can be transformed usingstandard curves, and the average of triplicate measurements used tocalculate the average and standard deviation for each patient. Thesevalues can be transformed before being used in the models, e.g.log-transformed, Box-Cox transformed (Box and Cox, Royal Stat. Soc.,Series B, 26:211-246(1964). The data are then input into a predictivemodel, which will classify the sample according to the state. Theresulting information can be communicated to a patient or health careprovider.

To generate a predictive model for preterm birth, a robust data set,comprising known control samples and samples corresponding to thepreterm birth classification of interest is used in a training set. Asample size can be selected using generally accepted criteria. Asdiscussed above, different statistical methods can be used to obtain ahighly accurate predictive model. Examples of such analysis are providedin Example 2.

In one embodiment, hierarchical clustering is performed in thederivation of a predictive model, where the Pearson correlation isemployed as the clustering metric. One approach is to consider a pretermbirth dataset as a “learning sample” in a problem of “supervisedlearning.” CART is a standard in applications to medicine (Singer,Recursive Partitioning in the Health Sciences, Springer (1999)) and canbe modified by transforming any qualitative features to quantitativefeatures; sorting them by attained significance levels, evaluated bysample reuse methods for Hotelling's T² statistic; and suitableapplication of the lasso method. Problems in prediction are turned intoproblems in regression without losing sight of prediction, indeed bymaking suitable use of the Gini criterion for classification inevaluating the quality of regressions.

This approach led to what is termed FlexTree (Huang, Proc. Nat. Acad.Sci. U.S.A 101:10529-10534(2004)). FlexTree performs very well insimulations and when applied to multiple forms of data and is useful forpracticing the claimed methods. Software automating FlexTree has beendeveloped. Alternatively, LARTree or LART can be used (Turnbull (2005)Classification Trees with Subset Analysis Selection by the Lasso,Stanford University). The name reflects binary trees, as in CART andFlexTree; the lasso, as has been noted; and the implementation of thelasso through what is termed LARS by Efron et al. (2004) Annals ofStatistics 32:407-451 (2004). See, also, Huang et al., Proc. Natl. Acad.Sci. USA. 101(29):10529-34 (2004). Other methods of analysis that can beused include logic regression. One method of logic regression Ruczinski,Journal of Computational and Graphical Statistics 12:475-512 (2003).Logic regression resembles CART in that its classifier can be displayedas a binary tree. It is different in that each node has Booleanstatements about features that are more general than the simple “and”statements produced by CART.

Another approach is that of nearest shrunken centroids (Tibshirani,Proc. Natl. Acad. Sci. U.S.A 99:6567-72(2002)). The technology isk-means-like, but has the advantage that by shrinking cluster centers,one automatically selects features, as is the case in the lasso, tofocus attention on small numbers of those that are informative. Theapproach is available as PAM software and is widely used. Two furthersets of algorithms that can be used are random forests (Breiman, MachineLearning 45:5-32 (2001)) and MART (Hastie, The Elements of StatisticalLearning, Springer (2001)). These two methods are known in the art as“committee methods,” that involve predictors that “vote” on outcome.

To provide significance ordering, the false discovery rate (FDR) can bedetermined. First, a set of null distributions of dissimilarity valuesis generated. In one embodiment, the values of observed profiles arepermuted to create a sequence of distributions of correlationcoefficients obtained out of chance, thereby creating an appropriate setof null distributions of correlation coefficients (Tusher et al., Proc.Natl. Acad. Sci. U.S.A 98, 5116-21 (2001)). The set of null distributionis obtained by: permuting the values of each profile for all availableprofiles; calculating the pair-wise correlation coefficients for allprofile; calculating the probability density function of the correlationcoefficients for this permutation; and repeating the procedure for Ntimes, where N is a large number, usually 300. Using the Ndistributions, one calculates an appropriate measure (mean, median,etc.) of the count of correlation coefficient values that their valuesexceed the value (of similarity) that is obtained from the distributionof experimentally observed similarity values at given significancelevel.

The FDR is the ratio of the number of the expected falsely significantcorrelations (estimated from the correlations greater than this selectedPearson correlation in the set of randomized data) to the number ofcorrelations greater than this selected Pearson correlation in theempirical data (significant correlations). This cut-off correlationvalue can be applied to the correlations between experimental profiles.Using the aforementioned distribution, a level of confidence is chosenfor significance. This is used to determine the lowest value of thecorrelation coefficient that exceeds the result that would have obtainedby chance. Using this method, one obtains thresholds for positivecorrelation, negative correlation or both. Using this threshold(s), theuser can filter the observed values of the pair wise correlationcoefficients and eliminate those that do not exceed the threshold(s).Furthermore, an estimate of the false positive rate can be obtained fora given threshold. For each of the individual “random correlation”distributions, one can find how many observations fall outside thethreshold range. This procedure provides a sequence of counts. The meanand the standard deviation of the sequence provide the average number ofpotential false positives and its standard deviation.

In an alternative analytical approach, variables chosen in thecross-sectional analysis are separately employed as predictors in atime-to-event analysis (survival analysis), where the event is theoccurrence of preterm birth, and subjects with no event are consideredcensored at the time of giving birth. Given the specific pregnancyoutcome (preterm birth event or no event), the random lengths of timeeach patient will be observed, and selection of proteomic and otherfeatures, a parametric approach to analyzing survival can be better thanthe widely applied semi-parametric Cox model. A Weibull parametric fitof survival permits the hazard rate to be monotonically increasing,decreasing, or constant, and also has a proportional hazardsrepresentation (as does the Cox model) and an accelerated failure-timerepresentation. All the standard tools available in obtainingapproximate maximum likelihood estimators of regression coefficients andcorresponding functions are available with this model.

In addition the Cox models can be used, especially since reductions ofnumbers of covariates to manageable size with the lasso willsignificantly simplify the analysis, allowing the possibility of anonparametric or semi-parametric approach to prediction of time topreterm birth. These statistical tools are known in the art andapplicable to all manner of proteomic data. A set of biomarker, clinicaland genetic data that can be easily determined, and that is highlyinformative regarding the probability for preterm birth and predictedtime to a preterm birth event in said pregnant female is provided. Also,algorithms provide information regarding the probability for pretermbirth in the pregnant female.

Accordingly, one skilled in the art understands that the probability forpreterm birth according to the invention can be determined using eithera quantitative or a categorical variable. For example, in practicing themethods of the invention the measurable feature of each of N biomarkerscan be subjected to categorical data analysis to determine theprobability for preterm birth as a binary categorical outcome.Alternatively, the methods of the invention may analyze the measurablefeature of each of N biomarkers by initially calculating quantitativevariables, in particular, predicted gestational age at birth. Thepredicted gestational age at birth can subsequently be used as a basisto predict risk of preterm birth. By initially using a quantitativevariable and subsequently converting the quantitative variable into acategorical variable the methods of the invention take into account thecontinuum of measurements detected for the measurable features. Forexample, by predicting the gestational age at birth rather than making abinary prediction of preterm birth versus term birth, it is possible totailor the treatment for the pregnant female. For example, an earlierpredicted gestational age at birth will result in more intensiveprenatal intervention, i.e. monitoring and treatment, than a predictedgestational age that approaches full term.

Among women with a predicted GAB of j days plus or minus k days, p(PTB)can estimated as the proportion of women in the PAPR clinical trial (seeExample 1) with a predicted GAB of j days plus or minus k days whoactually deliver before 37 weeks gestational age. More generally, forwomen with a predicted GAB of j days plus or minus k days, theprobability that the actual gestational age at birth will be less than aspecified gestational age, p(actual GAB<specified GAB), was estimated asthe proportion of women in the PAPR clinical trial with a predicted GABof j days plus or minus k days who actually deliver before the specifiedgestational age.

In the development of a predictive model, it can be desirable to selecta subset of markers, i.e. at least 3, at least 4, at least 5, at least6, up to the complete set of markers. Usually a subset of markers willbe chosen that provides for the needs of the quantitative sampleanalysis, e.g. availability of reagents, convenience of quantitation,etc., while maintaining a highly accurate predictive model. Theselection of a number of informative markers for building classificationmodels requires the definition of a performance metric and auser-defined threshold for producing a model with useful predictiveability based on this metric. For example, the performance metric can bethe AUC, the sensitivity and/or specificity of the prediction as well asthe overall accuracy of the prediction model.

As will be understood by those skilled in the art, an analyticclassification process can use any one of a variety of statisticalanalytic methods to manipulate the quantitative data and provide forclassification of the sample. Examples of useful methods include,without limitation, linear discriminant analysis, recursive featureelimination, a prediction analysis of microarray, a logistic regression,a CART algorithm, a FlexTree algorithm, a LART algorithm, a randomforest algorithm, a MART algorithm, and machine learning algorithms.

As described in Example 2, various methods are used in a training model.The selection of a subset of markers can be for a forward selection or abackward selection of a marker subset. The number of markers can beselected that will optimize the performance of a model without the useof all the markers. One way to define the optimum number of terms is tochoose the number of terms that produce a model with desired predictiveability (e.g. an AUC>0.75, or equivalent measures ofsensitivity/specificity) that lies no more than one standard error fromthe maximum value obtained for this metric using any combination andnumber of terms used for the given algorithm.

TABLE 1 Transitions with p-values less than 0.05in univariate Cox Proportional Hazardsanalyses to predict Gestational Age at Birth p-value Cox TransitionProtein univariate ITLPDFTGDLR_ LBP_HUMAN 0.006 624.34_920.4 ELLESYIDGR_THRB_HUMAN 0.006 597.8_710.3 TDAPDLPEENQAR_ CO5_HUMAN 0.007 728.34_613.3AFTECCVVASQLR_ CO5_HUMAN 0.009 770.87_574.3 SFRPFVPR_ LBP_HUMAN 0.011335.86_272.2 ITLPDFTGDLR_ LBP_HUMAN 0.012 624.34_288.2 SFRPF_ LBP_HUMAN0.015 VPR_ 335.86_63_5.3 ELLESYIDGR_ THRB_HUMAN 0.018 597.8_839.4LEQGENVFLQATDK_ C1QB_HUMAN 0.019 796.4_822.4 ETAASLLQAGYK_ THRB_HUMAN0.021 626.33_679.4 VTGWGNLK_ THRB_HUMAN 0.021 437.74_617.3 EAQLPV1ENK_PLMN_HUMAN 0.023 570.82_699.4 EAQLP_ PLMN_HUMAN 0.023 VIENK_570.82_329.1 FLQEQGHR_ CO8G_HUMAN 0.025 338.84_497.3 IRPFFPQQ_FIBB_HUMAN 0.028 516.79_661.4 ETAASLLQAGYK_ THRB_HUMAN 0.029626.33_879.5 AFTECCVVASQLR_ CO5_HUMAN 0.030 770.87_673.4 TLLPVSKPEIR_CO5_HUMAN 0.030 418.26_288.2 LSSPAVITDK_ PLMN_HUMAN 0.033 515.79_743.4YEVQGEVFTKPQLWP_ CRP_HUMAN 0.036 910.96_392.2 LQGTLPVEAR_ CO5_HUMAN0.036 542.31_571.3 VRPQQLVK_ ITIH4_HUMAN 0.036 484.31_609.3 IEEIAAK_CO5_HUMAN 0.041 387.22_531.3 TLLPVSKPEIR_ CO5__HUMAN 0.042 418.26_514.3VQEAHLTEDQIFYFPK_ CO8G_HUMAN 0.047 655.66_701.4 ISLLLIESWLEPVR_CSH_HUMAN 0.048 834.49_371.2 ALQDQLVLVAAK_ ANGT_HUMAN 0.048 634.88_289.2YEFLNGR_ PLMN_HUMAN 0.049 449.72_293.1

TABLE 2 Transitions selected by the Cox stepwise AIC analysis Transitioncoef exp(coef) se(coef) z Pr(>|z|) Collection.Window.  1.28E−01 1.14E+002.44E−02 5.26 1.40E−07 GA.in.Days ITLPDFTGDLR_  2.02E+00 7.52E+001.14E+00 1.77 0.07667 624.34_920.4 TPSAAYLWVGTGASEAEK  2.85E+01 2.44E+123.06E+00 9.31 <2e−16 919.45_849.4 TATSEYQTFFNPR_  5.14E+00 1.70E+026.26E−01 8.21 2.20E−16 781.37_386.2 TASDFITK_ −1.25E+00 2.86E−011.58E+00 −0.79 0.42856 441.73_781.4 IITGLLEFEVYLEYLQNR_  1.30E+014.49E+05 1.45E+00 9 <2e−16 738.4_530.3 IIGGSDADIK_ −6.43E+01 1.16E−286.64E+00 −9.68 <2e−16 494.77_762.4 YTTEIIK_  6.96E+01 1.75E+30 7.06E+009.86 <2e−16 434.25_603.4 EDTPNSVWEPAK_  7.91E+00 2.73E+03 2.66E+00 2.980.00293 686.82_3 15.2 LYYGDDEK_  8.74E+00 6.23E+03 1.57E+00 5.572.50E−08 501.72_726.3 VRPQQLVK_  4.64E+01 1.36E+20 3.97E+00 11.66 <2e−16484.31_609.3 GGEIEGFR_ −3.33E+00 3.57E−02 2.19E+00 −1.52 0.12792432.71_379.2 DGSPDVTTADIGANTP −1.52E+01 2.51E−07 1.41E+00 −10.8 <2e−16DATK_973.45_844.4 VQEAHLTEDQIFYFPK_ −2.02E+01 1.77E−09 2.45E+00 −8.222.20E−16 655.66_391.2 VEIDTK_  7.06E+00 1.17E+03 1.45E+00 4.86 1.20E−06352.7_476.3 AVLTIDEK_  7.85E+00 2.56E+03 9.46E−01 8.29 <2e−16444.76_605.3 FSVVYAK_ −2.44E+01 2.42E−11 3.08E+00 −7.93 2.20E−15407.23_579.4 YYLQGAK_ −1.82E+01 1.22E−08 2.45E+00 −7.44 1.00E−13421.72_516.3 EENFYVDETTVVK_ −1.90E+01 5.36E−09 2.71E+00 −7.03 2.00E−12786.88_259.1 YGFYTHVFR_  1.90E+01 1.71E+08 2.73E+00 6.93 4.20E−12397.2_421.3 HTLNQIDEVK_  1.03E+01 3.04E+04 2.11E+00 4.89 9.90E−07598.82_951.5 AFIQLWAFDAVK_  1.08E+01 4.72E+04 2.59E+00 4.16 3.20E−05704.89_836.4 SGFSFGFK43_8.72_  1.35E+01 7.32E+05 2.56E+00 5.27 1.40E−07585.3 GWVTDGFSSLK_ −3.12E+00 4.42E−02 9.16E−01 −3.4 0.00066 598.8_854.4ITENDIQIALDDAK_  1.91E+00 6.78E+00 1.36E+00 1.4 0.16036 779.9_632.3

TABLE 3 Transitions selected by Cox lasso model exp se Pr Transitioncoef (coef) (coef) z (>|z|) Collection. 0.0233 1.02357 0.00928 2.510.012 Window.GA. in.Days AFTECCVVAS 1.07568 2.93198 0.84554 1.27 0.203QLR_ 770.87_574.3 ELLESYIDGR_ 1.3847 3.99365 0.70784 1.96 0.05597.8_710.3 ITLPDFTGDLR_ 0.814 2.25691 0.40652 2 0.045 624.34_920.4

TABLE 4 Area under the ROC (AUROC) curvefor individual analytes to pre-term  birth subjects from non-pre-term birth subjects. The 77 transitions discriminate with the highest AUROC are aare shown. Transition AUROC ELLES_YIDGR_597.8_710.3 0.71AFTECCWASQLR_770.87_574.3 0.70 ITLPDFTGDLR_624.34_920.4 0.70IRPFFPQQ_516.79_661.4 0.68 TDAPDLPEENQ_AR_728.34_613.3 0.67ITLPDFTGDLR_624.34_288.2 0.67 ELLESYIDGR_597.8_839.4 0.67SFRPFVPR_3_35.86_635.3 0.67 ETAASLLQAGYK_626.33_879.5 0.67TLLPVSKPEIR_418.26_288.2 0.66 ETAASLLQAGYK_626.33_679.4 0.66SFRPFVPR_335.86_272.2 0.66 LQGTLP_VEAR542.31_571.3 0.66VEPLYELVTATDFAYSSTV 0.66 R_754.38_712.4 DPDQTDGLGLSYLSSHIANVE 0.66R_796.39_328.1 VTGWGNLK_437.74_617.3 0.65 ALQDQLVLVAAK_634.88_289.2 0.65EAQLPVTENK_570.82_329.1 0.65 VRPQQLVK_484.31_609.3 0.65AFTECCWASQLR_770.87_673.4 0.65 YEFLNGR_449.72_293.1 0.65VGEYSLYIGR_578.8_871.5 0.64 EAQLPVIENK_570.82_699.4 0.64TLLPVSKPEIR_418.26_514.3 0.64 IEEIAAK_387.22_531.3 0.64LEQGENVFLQATDK_796.4_822.4 0.64 LQGTLPVEAR_542.31_842.5 0.64FLQEQGHR_338.84_497.3 0.63 ISLLLIESWLEPVR_834.49_371.2 0.63IITGLLEFEVYLEYLQNR_738.4_530.3 0.63 LSSPAVITDK515.79_743.4 0.63VRPQQLVK_484.31_722.4 0.63 SLPVSDSVLSGFEQR_810.92_723.3 0.63VQEAHLTEDQIFYFPK_655.66_701.4 0.63 NADYSYSVWK_616.78_333.2 0.63DAQYAPGYDK_564.25_813.4 0.62 FQLPGQK_409.23_276.1 0.62TASDFITK_441.73_781.4 0.62 YGLVTYATYPK_638.33_334.2 0.62GSFALSFPVESDVAPIAR_931.99_363.2 0.62 TLLIANETLR_572.34_703.4 0.62VILGAHQEVNLEPFIVQEIEVS 0.62 R_832.78_860.4 TATSEYQTFFNPR_781.37_386.20.62 YEVQGEVFTKPQLWP_910.96_392.2 0.62 DISEVVTPR_508.27_472.3 0.62GSFALSFPVESDVAPIAR_931.99_456.3 0.62 YGFYTHVFR_397.2_421.3 0.62TLEAQLTPR_514.79_685.4 0.62 YGFYTHVFR_397.2_659.4 0.62AVGYLITGYQR_620.84_737.4 0.61 DPDQTDGLGLSYLSSHIAN 0.61 VER_796.39_456.2FNAVLTNPQGDYDTSTGK_964.46_262.1 0.61 SPEQQETVLDGNLIIR_906.48_685.4 0.61ALNFELPLEYNSALYSR_620.99_538.3 0.61 GGEIEGFR_432.71_508.3 0.61GIVEECCFR_585.26_900.3 0.61 DAQYAPGYDK_564.25_315.1 0.61FAFNLYR_465.75_712.4 0.61 YTTEIIK_434.25_603.4 0.61AVLTIDEK_444.76_605.3 0.61 AITPPHPASQANIIFDITEG 0.60 NLR_825.77_459.3EPGLCTWQSLR_673.83_790.4 0.60 AVYEAVLR_460.76_587.4 0.60ALQDQLVLVAAK_634.88_956.6 0.60 AWVAWR_394.71_531.3 0.60TNLESILSYPK_632.84_807.5 0.60 HLSLLTTLSNR_418.91_376.2 0.60FTFTLHLETPKPSISSSNLNP 0.60 R_829.44_787.4 AVGYLITGYQR_620.84_523.3 0.60FQLPGQK_409.23_429.2 0.60 YGLVTYATYPK_638.33_843.4 0.60TELRPGETLNVNFLLR_624.68_662.4 0.60 LSSPAVITDK_515.79_830.5 0.60TATSEYQTFFNPR_781.37_272.2 0.60 LPTAVVPLR_483.31_385.3 0.60APLTKPLK_289.86_260.2 0.60

TABLE 5 AUROCs for random forest, boosting, lasso,and logistic regression models for aspecific number of transitions permittedin the model, as estimated by 100 rounds of bootstrap resampling.Number of transitions rf boosting logit lasso 1 0.59 0.67 0.64 0.69 20.66 0.70 0.63 0.68 3 0.69 0.70 0.58 0.71 4 0.68 0.72 0.58 0.71 5 0.730.71 0.58 0.68 6 0.72 0.72 0.56 0.68 7 0.74 0.70 0.60 0.67 8 0.73 0.720.62 0.67 9 0.72 0.72 0.60 0.67 10 0.74 0.71 0.62 0.66 11 0.73 0.69 0.580.67 12 0.73 0.69 0.59 0.66 13 0.74 0.71 0.57 0.66 14 0.73 0.70 0.570.65 15 0.72 0.70 0.55 0.64

TABLE 6 Top 15 transitions selected by eachmultivariate method, ranked by importance for that method. rf boostinglasso logit 1 ELLES AFTEC AFTEC ALQDQ YIDGR_ CVVAS CVVAS LVLVA 597.8_QLR_ QLR_ AK_ 710.3 770.87_ 770.87_ 634.88_ 574.3 574.3 289.2 2 TATSEDPDQT ISLLL AVLTI YQTFF DGLGL IESWL DEK_ NPR_ SYLSS EPVR_ 444.76_781.37_ HIANV 834.49_ 605.3 386.2 ER_ 371.2 796.39_ 328.1 3 ITLPD ELLESLPTAV Collection. FTGDL YIDGR_ VPLR_ Window. R_ 597.8_ 483.31_GA.in.Days 624.34_ 710.3 385.3 920.4 4 AFTEC TATSE ALQDQ AHYDL CVVASYQTFF LVLVA R_ QLR_ NPR_ AK_ 387.7_ 770.87_ 781.37_ 634.88_ 566.3 574.3386.2 289.2 5 VEPLY ITLPD ETAAS AEAQA ELVTA FTGDL LLQAG QYSAA TDFAY R_YK_ VAK_ SSTVR_ 624.34_ 626.33_ 654.33_ 754.38_ 920.4 679.4 908.5 712.46 GSFAL GGEIE IITGL AEAQA SFPVE GFR_ LEFEV QYSAA SDVAP 432.71_ YLEYLVAK_ IAR_ 379.2 QNR_ 654.33_ 931.99_ 738.4_ 709.4 363.2 530.3 7 VGEYSALQDQ ADSQA ADSQA LYIGR_ LVLVA QLLLS QLLLS 578.8_ AK_ TVVGV TVVGV 871.5634.88_ FTAPG FTAPG 289.2 LHLK_ LHLK_ 822.46_ 822.46_ 983.6 983.6 8SFRPF VGEYS SLPVS AITPP VPR_ LYIGR_ DSVLS HPASQ 33586_ 578.8_ GFEQR_ANIIF 635.3 871.5 810.92_ DITEG 723.3 NLR_ 825.77_ 459.3 9 ALQDQ VEPLYSFRPF ADSQA LVLVA ELVTA VPR_ QLLLS AK_ TDFAY 335.86_ TVVGV 634.88_SSTVR_ 272.2 FTAPG 289.2 754.38_ LHLK_ 712.4 822.46_ 664.4 10 EDTPNSPEQQ IIGGS AYSDL SVWEP ETVLD DADIK_ SR_ AK_ GNLII 494.77_ 406.2_686.82_ R_ 260.2 375.2 315.2 906.48_ 685.4 11 YGFYT YEFLN NADYS DALSSHVFR_ GR_ YSVWK_ VQESQ 397.2_ 449.72_ 616.78_ VAQQA 421.3 293.1 333.2 R_572.96_ 672.4 12 DPDQT LEQGE GSFAL ANRPF DGLGL NVFLQ SFPVE LVFIR_ SYLSSATDK_ SDVAP 411.58_ HIANV 796.4_ IAR_ 435.3 ER_ 822.4 931_ 796.39_ 99_328.1 456.3 13 LEQGE LQGTL LSSPA DALSS NVFLQ PVEAR_ VITDK_ VQESQ ATDK_542.31_ 515.79_ VAQQA 796.4_ 571.3 743.4 R_ 822.4 572.96_ 502.3 14 LQGTLISLLL ELPEH ALEQD PVEAR_ IESWL TVK_ LPVNI 542.31_ EPVR_ 476.76_ K_ 571.3834.49_ 347.2 620.35_ 371.2 570.4 15 SFRPF TASDF EAQLP AVLTI VPR_ ITK_VIENK_ DEK_ 335.86_ 441.73_ 570.82_ 444.76_ 272.2 781.4 699.4 718.4

In yet another aspect, the invention provides kits for determiningprobability of preterm birth, wherein the kits can be used to detect Nof the isolated biomarkers listed in Tables 1 through 63. For example,the kits can be used to detect one or more, two or more, or three of theisolated biomarkers selected from the group consisting of AFTECCVVASQLR,ELLESYIDGR, and ITLPDFTGDLR. For example, the kits can be used to detectone or more, two or more, or three of the isolated biomarkers selectedfrom the group consisting of FLNWIK, FGFGGSTDSGPIR, LLELTGPK,VEHSDLSFSK, IEGNLIFDPNNYLPK, ALVLELAK, TQILEWAAER, DVLLLVHNLPQNLPGYFWYK,SEPRPGVLLR, ITQDAQLK, ALDLSLK, WWGGQPLWITATK, and LSETNR.

In another aspect, the kits can be used to detect one or more, two ormore, three or more, four or more, five or more, six or more, seven ormore, or eight of the isolated biomarkers selected from the groupconsisting of lipopolysaccharide-binding protein (LBP), prothrombin(THRB), complement component C5 (C5 or CO5), plasminogen (PLMN), andcomplement component C8 gamma chain (C8G or CO8G).

In another aspect, the kits can be used to detect one or more, two ormore, three or more, four or more, five or more, six or more, seven ormore, or eight of the isolated biomarkers selected from the groupconsisting of Alpha-1B-glycoprotein (A1BG), Disintegrin andmetalloproteinase domain-containing protein 12 (ADA12), ApolipoproteinB-100 (APOB), Beta-2-microglobulin (B2MG), CCAAT/enhancer-bindingprotein alpha/beta (HP8 Peptide), Corticosteroid-binding globulin (CBG),Complement component C6, Endoglin (EGLN), Ectonucleotidepyrophosphatase/phosphodiesterase family member 2 (ENPP2), Coagulationfactor VII (FA7), Hyaluronan-binding protein 2 (HABP2),Pregnancy-specific beta-1-glycoprotein 9 (PSG9), Inhibin beta E chain(INHBE).

The kit can include one or more agents for detection of biomarkers, acontainer for holding a biological sample isolated from a pregnantfemale; and printed instructions for reacting agents with the biologicalsample or a portion of the biological sample to detect the presence oramount of the isolated biomarkers in the biological sample. The agentscan be packaged in separate containers. The kit can further comprise oneor more control reference samples and reagents for performing animmunoassay.

In one embodiment, the kit comprises agents for measuring the levels ofat least N of the isolated biomarkers listed in Tables 1 through 63. Thekit can include antibodies that specifically bind to these biomarkers,for example, the kit can contain at least one of an antibody thatspecifically binds to lipopolysaccharide-binding protein (LBP), anantibody that specifically binds to prothrombin (THRB), an antibody thatspecifically binds to complement component C5 (C5 or CO5), an antibodythat specifically binds to plasminogen (PLMN), and an antibody thatspecifically binds to complement component C8 gamma chain (C8G or CO8G).

In one embodiment, the kit comprises agents for measuring the levels ofat least N of the isolated biomarkers listed in Tables 1 through 63. Thekit can include antibodies that specifically bind to these biomarkers,for example, the kit can contain at least one of an antibody thatspecifically binds to Alpha-1B-glycoprotein (A1BG), Disintegrin andmetalloproteinase domain-containing protein 12 (ADA12), ApolipoproteinB-100 (APOB), Beta-2-microglobulin (B2MG), CCAAT/enhancer-bindingprotein alpha/beta (HP8 Peptide), Corticosteroid-binding globulin (CBG),Complement component C6, Endoglin (EGLN), Ectonucleotidepyrophosphatase/phosphodiesterase family member 2 (ENPP2), Coagulationfactor VII (FA7), Hyaluronan-binding protein 2 (HABP2),Pregnancy-specific beta-1-glycoprotein 9 (PSG9), Inhibin beta E chain(INHBE).

The kit can comprise one or more containers for compositions containedin the kit. Compositions can be in liquid form or can be lyophilized.Suitable containers for the compositions include, for example, bottles,vials, syringes, and test tubes. Containers can be formed from a varietyof materials, including glass or plastic. The kit can also comprise apackage insert containing written instructions for methods ofdetermining probability of preterm birth.

From the foregoing description, it will be apparent that variations andmodifications can be made to the invention described herein to adopt itto various usages and conditions. Such embodiments are also within thescope of the following claims.

The recitation of a listing of elements in any definition of a variableherein includes definitions of that variable as any single element orcombination (or subcombination) of listed elements. The recitation of anembodiment herein includes that embodiment as any single embodiment orin combination with any other embodiments or portions thereof.

All patents and publications mentioned in this specification are hereinincorporated by reference to the same extent as if each independentpatent and publication was specifically and individually indicated to beincorporated by reference.

The following examples are provided by way of illustration, notlimitation.

EXAMPLES Example 1. Development of Sample Set for Discovery andValidation of Biomarkers for Preterm Birth

A standard protocol was developed governing conduct of the ProteomicAssessment of Preterm Risk (PAPR) clinical study. This protocol alsospecified that the samples and clinical information could be used tostudy other pregnancy complications for some of the subjects. Specimenswere obtained from women at 11 Internal Review Board (IRB) approvedsites across the United States. After providing informed consent, serumand plasma samples were obtained, as well as pertinent informationregarding the patient's demographic characteristics, past medical andpregnancy history, current pregnancy history and concurrent medications.Following delivery, data were collected relating to maternal and infantconditions and complications. Serum and plasma samples were processedaccording to a protocol that requires standardized refrigeratedcentrifugation, aliquoting of the samples into 0.5 ml 2-D bar-codedcryovials and subsequent freezing at −80° C.

Following delivery, preterm birth cases were individually reviewed todetermine their status as either a spontaneous preterm birth or amedically indicated preterm birth. Only spontaneous preterm birth caseswere used for this analysis. For discovery of biomarkers of pretermbirth, 80 samples were analyzed in two gestational age groups: a) a latewindow composed of samples from 23-28 weeks of gestation which included13 cases, 13 term controls matched within one week of sample collectionand 14 term random controls, and, b) an early window composed of samplesfrom 17-22 weeks of gestation included 15 cases, 15 term controlsmatched within one week of sample collection and 10 random termcontrols.

The samples were subsequently depleted of high abundance proteins usingthe Human 14 Multiple Affinity Removal System (MARS 14), which removes14 of the most abundant proteins that are treated as uninformative withregard to the identification for disease-relevant changes in the serumproteome. To this end, equal volumes of each clinical or a pooled humanserum sample (HGS) sample were diluted with column buffer and filteredto remove precipitates. Filtered samples were depleted using a MARS-14column (4.6×100 mm, Cat. #5188-6558, Agilent Technologies). Samples werechilled to 4° C. in the autosampler, the depletion column was run atroom temperature, and collected fractions were kept at 4° C. untilfurther analysis. The unbound fractions were collected for furtheranalysis.

A second aliquot of each clinical serum sample and of each HGS wasdiluted into ammonium bicarbonate buffer and depleted of the 14 high andapproximately 60 additional moderately abundant proteins using anIgY14-SuperMix (Sigma) hand-packed column, comprised of 10 mL of bulkmaterial (50% slurry, Sigma). Shi et al., Methods, 56(2):246-53 (2012).Samples were chilled to 4° C. in the autosampler, the depletion columnwas run at room temperature, and collected fractions were kept at 4° C.until further analysis. The unbound fractions were collected for furtheranalysis.

Depleted serum samples were denatured with trifluorethanol, reduced withdithiotreitol, alkylated using iodoacetamide, and then digested withtrypsin at a 1:10 trypsin: protein ratio. Following trypsin digestion,samples were desalted on a C18 column, and the eluate lyophilized todryness. The desalted samples were resolubilized in a reconstitutionsolution containing five internal standard peptides.

Depleted and trypsin digested samples were analyzed using a scheduledMultiple Reaction Monitoring method (sMRM). The peptides were separatedon a 150 mm×0.32 mm Bio-Basic C18 column (ThermoFisher) at a flow rateof 5 μl/min using a Waters Nano Acquity UPLC and eluted using anacetonitrile gradient into a AB SCIEX QTRAP 5500 with a Turbo V source(AB SCIEX, Framingham, Mass.). The sMRM assay measured 1708 transitionsthat correspond to 854 peptides and 236 proteins. Chromatographic peakswere integrated using Rosetta Elucidator software (Ceiba Solutions).

Transitions were excluded from analysis, if their intensity area countswere less than 10000 and if they were missing in more than three samplesper batch. Intensity area counts were log transformed and MassSpectrometry run order trends and depletion batch effects were minimizedusing a regression analysis.

Example 2. Analysis I of Transitions to Identify Preterm BirthBiomarkers

The objective of these analyses was to examine the data collected inExample 1 to identify transitions and proteins that predict pretermbirth. The specific analyses employed were (i) Cox time-to-eventanalyses and (ii) models with preterm birth as a binary categoricaldependent variable. The dependent variable for all the Cox analyses wasGestational Age of time to event (where event is preterm birth). For thepurpose of the Cox analyses, preterm birth subjects have the event onthe day of birth. Term subjects are censored on the day of birth.Gestational age on the day of specimen collection is a covariate in allCox analyses.

The assay data were previously adjusted for run order and depletionbatch, and log transformed. Values for gestational age at time of samplecollection were adjusted as follows. Transition values were regressed ongestational age at time of sample collection using only controls(non-pre-term subjects). The residuals from the regression weredesignated as adjusted values. The adjusted values were used in themodels with pre-term birth as a binary categorical dependent variable.Unadjusted values were used in the Cox analyses.

Univariate Cox Proportional Hazards Analyses

Univariate Cox Proportional Hazards analyses was performed to predictGestational Age at Birth, including Gestational age on the day ofspecimen collection as a covariate. Table 1 shows the transitions withp-values less than 0.05. Five proteins have multiple transitions amongthose with p-value less than 0.05: lipopolysaccharide-binding protein(LBP), prothrombin (THRB), complement component C5 (C5 or CO5),plasminogen (PLMN), and complement component C8 gamma chain (C8G orCO8G).

Multivariate Cox Proportional Hazards Analyses: Stepwise AIC selection

Cox Proportional Hazards analyses was performed to predict GestationalAge at Birth, including Gestational age on the day of specimencollection as a covariate, using stepwise and lasso models for variableselection. These analyses include a total of n=80 subjects, with numberof PTB events=28. The stepwise variable selection analysis used theAkaike Information Criterion (AIC) as the stopping criterion. Table 2shows the transitions selected by the stepwise AIC analysis. Thecoefficient of determination (R²) for the stepwise AIC model is 0.86(not corrected for multiple comparisons).

Multivariate Cox Proportional Hazards Analyses: Lasso Selection

Lasso variable selection was used as the second method of multivariateCox Proportional Hazards analyses to predict Gestational Age at Birth,including Gestational age on the day of specimen collection as acovariate. This analysis uses a lambda penalty for lasso estimated bycross validation. Table 3 shows the results. The lasso variableselection method is considerably more stringent than the stepwise AIC,and selects only 3 transitions for the final model, representing 3different proteins. These 3 proteins give the top 4 transitions from theunivariate analysis; 2 of the top 4 univariate are from the sameprotein, and hence are not both selected by the lasso method. Lassotends to select a relatively small number of variables with low mutualcorrelation. The coefficient of determination (R²) for the lasso modelis 0.21 (not corrected for multiple comparisons).

Univariate AUROC Analysis of Preterm Birth as a Binary CategoricalDependent Variable

Univariate analyses was performed to discriminate pre-term subjects fromnon-pre-term subjects (pre-term as a binary categorical variable) asestimated by area under the receiver operating characteristic (AUROC)curve. These analyses use transition values adjusted for gestational ageat time of sample collection, as described above. Table 4 shows theAUROC curve for the 77 transitions with the highest AUROC area of 0.6 orgreater.

Multivariate Analysis of Preterm Birth as a Binary Categorical DependentVariable

Multivariate analyses was performed to predict preterm birth as a binarycategorical dependent variable, using random forest, boosting, lasso,and logistic regression models. Random forest and boosting models growmany classification trees. The trees vote on the assignment of eachsubject to one of the possible classes. The forest chooses the classwith the most votes over all the trees.

For each of the four methods (random forest, boosting, lasso, andlogistic regression) each method was allowed to select and rank its ownbest 15 transitions. We then built models with 1 to 15 transitions. Eachmethod sequentially reduces the number of nodes from 15 to 1independently. A recursive option was used to reduce the number of nodesat each step: To determine which node to remove, the nodes were rankedat each step based on their importance from a nested cross-validationprocedure. The least important node was eliminated. The importancemeasures for lasso and logistic regression are z-values. For randomforest and boosting, the variable importance was calculated frompermuting out-of-bag data: for each tree, the classification error rateon the out-of-bag portion of the data was recorded; the error rate wasthen recalculated after permuting the values of each variable (i.e.,transition); if the transition was in fact important, there would havebeen be a big difference between the two error rates; the differencebetween the two error rates were then averaged over all trees, andnormalized by the standard deviation of the differences. The AUCs forthese models are shown in Table 5, as estimated by 100 rounds ofbootstrap resampling. Table 6 shows the top 15 transitions selected byeach multivariate method, ranked by importance for that method. Thesemultivariate analyses suggest that models that combine 3 or moretransitions give AUC greater than 0.7, as estimated by bootstrap.

In multivariate models, random forest (rf), boosting, and lasso modelsgave the best area under the AUROC curve. The following transitions wereselected by these models, as significant in Cox univariate models,and/or having high univariate ROC'S:

AFTECCVVASQLR770.87_574.3 ELLESYIDGR_597.8_710.3 ITLPDFTGDLR_624.34920.4TDAPDLPEENQAR_728.34613.3 SFRPFVPR_335.86_635.3

In summary, univariate and multivariate Cox analyses was performed usingtransitions to predict Gestational Age at Birth (GAB), includingGestational age on the day of specimen collection as a covariate. In theunivariate Cox analysis, five proteins were identified that havemultiple transitions among those with p-value less than 0.05:lipopolysaccharide-binding protein (LBP), prothrombin (THRB), complementcomponent C5 (C5 or CO5), plasminogen (PLMN), and complement componentC8 gamma chain (C8G or CO8G).

In multivariate Cox analyses, stepwise AIC variable analysis selects 24transitions, while the lasso model selects 3 transitions, which includethe 3 top proteins in the univariate analysis. Univariate (AUROC) andmultivariate (random forest, boosting, lasso, and logistic regression)analyses were performed to predict pre-term birth as a binarycategorical variable. Univariate analyses identified 63 analytes withAUROC of 0.6 or greater. Multivariate analyses suggest that models thatcombine 3 or more transitions give AUC greater than 0.7, as estimated bybootstrap.

Example 3. Study II to Identify and Confirm Preterm Birth Biomarkers

A further study was performed using essentially the same methodsdescribed in the preceding Examples unless noted below. In this study, 2gestational aged matched controls were used for each case of 28 casesand 56 matched controls, all from the early gestational window only(17-22 weeks).

The samples were processed in 4 batches with each batch composed of 7cases, 14 matched controls and 3 HGS controls. Serum samples weredepleted of the 14 most abundant serum samples by MARS14 as described inExample 1. Depleted serum was then reduced with dithiothreitol,alkylated with iodacetamide, and then digested with trypsin at a 1:20trypsin to protein ratio overnight at 37° C. Following trypsindigestion, the samples were desalted on an Empore C18 96-well SolidPhase Extraction Plate (3M Company) and lyophilized to dryness. Thedesalted samples were resolubilized in a reconstitution solutioncontaining five internal standard peptides.

The LC-MS/MS analysis was performed with an Agilent Poroshell 120 EC-C18column (2.1×50 mm, 2.7 μm) and eluted with an acetonitrile gradient intoa Agilent 6490 Triple Quadrapole mass spectrometer.

Data analysis included the use of conditional logistic regression whereeach matching triplet (case and 2 matched controls) was a stratum. Thep-value reported in the table indicates whether there is a significantdifference between cases and matched controls.

TABLE 7 Results of Study II Transi- tion Protein Annotation p-valueDFHIN CFAB_ Complement 0.006729512 LFQVL HUMAN factor B PWLK ITLPD LBP_Lipopolysaccharide- 0.012907017 FTGDL HUMAN binding R protein WWGGQENPP2_ Ectonucleotide 0.013346 PLWIT HUMAN pyrophosphatase/ ATKPhosphodiesterase family member 2 TASDF GELS_ Gelsolin 0.013841221 ITKHUMAN AGLLR PGRP2_ N-acetylmuramoyl- 0.014241979 PDYAL HUMAN L-alanineLGHR amidase FLQEQ CO8G_ Complement 0.014339596 GHR HUMANcomponent C8 gamma chain FLNWI HABP2_ Hyaluronan-binding 0.014790418 KHUMAN protein 2 EKPAG BPIB1_ BPI fold- 0.019027746 GIPVL HUMANcontaining GSLVN family B TVLK member 1 ITGFL LBP_ Lipopolysaccharide-0.019836986 KPGK HUMAN binding protein YGLVT CFAB_ Complement0.019927774 YATYP HUMAN factor B K SLLQP CO8A_ Complement 0.020930939 NKHUMAN component C8 alpha chain DISEV CFAB_ Complement 0.021738046 VTPRHUMAN factor B VQEAH CO8G_ Complement 0.021924548 LTEDQ HUMANcomponent C8 IFYFP gamma chain K SPELQ APOA2_ Apolipoprotein 0.025944285AEAK HUMAN A-II TYLHT ENPP2_ Ectonucleotide 0.026150038 YESEI HUMANpyrophosphatase/ phosphodiesterase family member 2 DSPSV PROF1_Profilin-1 0.026607371 WAAVP HUMAN GK HYINL NPY_ Pro-neuropeptide0.027432804 ITR HUMAN Y SLPVS CO8G_ Complement 0.029647857 DSVLS HUMANcomponent C8 GFEQR gamma chain IPGIF CO8B_ Complement 0.030430996 ELGISHUMAN component SQSDR C8 beta chain IQTHS F13B_ Coagulation 0.031667664TTYR HUMAN factor XIII B chain DGSPD PGRP2_ N-acetylmuramoyl-0.034738338 VTTAD HUMAN L-alanine amidase IGANT PDATK QLGLP ITIH4_Inter-alpha- 0.043130591 GPPDV HUMAN trypsin PDHAA inhibitor YHPF heavychain H4 FPLGS LCAP_ Leucyl-cystinyl 0.044698045 YTIQN HUMANaminopeptidase IVAGS TYLFS TK AHYDL FETUA_ Alpha-2-HS- 0.046259201 RHUMAN glycoprotein SFRPF LBP_ Lipopolysaccharide- 0.047948847 VPR HUMANbinding protein

Example 4. Study III Shotgun Identification of Preterm Birth Biomarkers

A further study used a hypothesis-independent shotgun approach toidentify and quantify additional biomarkers not present on ourmultiplexed hypothesis dependent MRM assay. Samples were processed asdescribed in the preceding Examples unless noted below.

Tryptic digests of MARS depleted patient (preterm birth cases and termcontrols) samples were fractionated by two-dimensional liquidchromatography and analyzed by tandem mass spectrometry. Aliquots of thesamples, equivalent to 3-4 μl of serum, were injected onto a 6 cm×75 μmself-packed strong cation exchange (Luna SCX, Phenomenex) column.Peptides were eluded from the SCX column with salt (15, 30, 50, 70, and100% B, where B=250 mM ammonium acetate, 2% acetonitrile, 0.1% formicacid in water) and consecutively for each salt elution, were bound to a0.5 μl C18 packed stem trap (Optimize Technologies, Inc.) and furtherfractionated on a 10 cm×75 μm reversed phase ProteoPep II PicoFritcolumn (New Objective). Peptides were eluted from the reversed phasecolumn with an acetonitrile gradient containing 0.1% formic acid anddirectly ionized on an LTQ-Orbitrap (ThermoFisher). For each scan,peptide parent ion masses were obtained in the Orbitrap at 60Kresolution and the top seven most abundant ions were fragmented in theLTQ to obtain peptide sequence information.

Parent and fragment ion data were used to search the Human RefSeqdatabase using the Sequest (Eng et al., J. Am. Soc. Mass Spectrom 1994;5:976-989) and X! Tandem (Craig and Beavis, Bioinformatics 2004;20:1466-1467) algorithms. For Sequest, data was searched with a 20 ppmtolerance for the parent ion and 1 AMU for the fragment ion. Two missedtrypsin cleavages were allowed, and modifications included staticcysteine carboxyamidomethylation and methionine oxidation. Aftersearching the data was filtered by charge state vs. Xcorr scores(charge+1≥1.5 Xcorr, charge+2≥2.0, charge+3≥2.5). Similar searchparameters were used for X!tandem, except the mass tolerance for thefragment ion was 0.8 AMU and there is no Xcorr filtering. Instead, thePeptideProphet algorithm (Keller et al., Anal. Chem 2002; 74:5383-5392)was used to validate each X!Tandem peptide-spectrum assignment andProtein assignments were validated using ProteinProphet algorithm(Nesvizhskii et al., Anal. Chem 2002; 74:5383-5392). Data was filteredto include only the peptide-spectrum matches that had PeptideProphetprobability of 0.9 or more. After compiling peptide and proteinidentifications, spectral count data for each peptide were imported intoDAnTE software (Polpitiya et al., Bioinformatics. 2008; 24:1556-1558).Log transformed data was mean centered and missing values were filtered,by requiring that a peptide had to be identified in at least 4 cases and4 controls. To determine the significance of an analyte, ReceiverOperating Characteristic (ROC) curves for each analyte were createdwhere the true positive rate (Sensitivity) is plotted as a function ofthe false positive rate (1-Specificity) for different thresholds thatseparate the SPTB and Term groups. The area under the ROC curve (AUC) isequal to the probability that a classifier will rank a randomly chosenpositive instance higher than a randomly chosen negative one. Peptideswith AUC greater than or equal to 0.6 found uniquely by Sequest orXtandem are found in Tables 8 and 9, respectively, and those identifiedby both approaches are found in Table 10.

TABLE 8 Significant peptides (AUC > 0.6) for Sequest only Uniprot ID S_Protein Description (name) Peptide AUC 5'-AMP-activated Q9UGI9K.LVIFDTM*L 0.78 protein kinase (AAKG3_ EIK.K subunit gamma-3 HUMAN)afamin precursor P43652 K.FIEDNIEYIT 0.79 (AFAM_ IIAFAQYVQEAT HUMAN)FEEMEK.L afamin precursor P43652 K.IAPQLSTEEL 0.71 (AFAM_ VSLGEK.MHUMAN) afamin precursor P43652 K.LKHELTDEE 0.60 (AFAM_ LQSLFTNFANVHUMAN) VDK.C afamin precursor P43652 K.LPNNVLQEK.I 0.60 (AFAM_ HUMAN)afamin precursor P43652 K.SDVGFLPPFPT 0.71 (AFAM_ LDPEEK.C HUMAN)afamin precursor P43652 K.VMNHICSK.Q 0.68 (AFAM_ HUMAN) afamin precursorP43652 R.ESLLNHFLY 0.69 (AFAM_ EVAR.R HUMAN) afamin precursor P43652R.LCFFYNKK.S 0.69 (AFAM_ HUMAN) alpha-1- P01011 K.AVLDVFEEGT 0.72antichymotrypsin (AACT_ EASAATAVK.I HUMAN) alpha-1- P01011 K.EQLSLLDR.F0.65 antichymotrypsin (AACT_ precursor HUMAN) alpha-1- P01011K.EQLSLLDRFTE 0.64 antichymotrypsin (AACT_ DAK.R precursor HUMAN)alpha-1- P01011 K.EQLSLLDRFT 0.60 antichymotrypsin (AACT_ EDAKR.Lprecursor HUMAN) alpha-1- P01011 K.ITDLIKDLDSQT 0.65 antichymotrypsin(AACT_ MM*VLVNYIFFK.A precursor HUMAN) alpha-1- P01011 K.ITLLSALVET 0.62antichymotrypsin (AACT_ R.T precursor HUMAN) alpha-1- P01011K.RLYGSEAFATDF 0.62 antichymotrypsin (AACT_ QDSAAAK.K precursor HUMAN)alpha-1- P01011 R.EIGELYLPK.F 0.65 antichymotrypsin (AACT_ precursorHUMAN) alpha-lB- P04217 R.CEGPIPDVTFE 0.67 glycoprotein (A1BG_ LLR.Eprecursor HUMAN) alpha-lB- P04217 R.FALVR.E 0.79 glycoprotein (A1BG_precursor HUMAN) alpha-2- P08697 K.SPPGVCSR.D 0.81 antiplasmin (A2AP_isoform a HUMAN) precursor alpha-2- P08697 R.DSFHLDEQFTV 0.69antiplasmin (A2AP_ PVEMMQAR.T isoform a HUMAN) precursor alpha-2-HS-P02765 K.CNLLAEK.Q 0.67 glycoprotein (FETUA_ preproprotein HUMAN)alpha-2-HS- P02765 K.EHAVEGDCDFQ 0.67 glycoprotein (FETUA_ LLK.Lpreproprotein HUMAN) alpha-2-HS- P02765 K.HTLNQIDEVKV 0.64 glycoprotein(FETUA_ WPQQPSGELFEIE preproprotein HUMAN) IDTLETTCHVLDP TPVAR.Calpha-2- P01023 K.MVSGFIPLK 0.73 macroglobulin (A2MG_ PTVK.M precursorHUMAN) alpha-2- P01023 R.AFQPFFVELT 0.68 macroglobulin (A2MG_ M*PYSVIR.Gprecursor HUMAN) alpha-2- P01023 R.AFQPFFVEL 0.62 macroglobulin (A2MG_TMPYSVIR.G precursor HUMAN) alpha-2- P01023 R.NQGNTWLTA 0.73macroglobulin (A2MG_ FVLK.T precursor HUMAN) angiotensinogen P01019K.IDRFMQAVT 0.81 preproprotein (ANGT_ GWK.T HUMAN) angiotensinogenP01019 K.LDTEDKLR.A 0.72 preproprotein (ANGT_ HUMAN) angiotensinogenP01019 K.TGCSLMGASV 0.64 preproprotein (ANGT_ DSTLAF HUMAN) NTYVHFQGK.Mangiotensinogen P01019 R.AAMVGMLANF 0.62 preproprotein (ANGT_ LGFR.IHUMAN) antithrombin-III P01008 K.NDNDNIFLS 0.64 precursor (ANT3_ PLSISTHUMAN) AFAMTK.L antithrombin-III P01008 K.SKLPGIVA 0.81 precursor (ANT3_EGRDDLY HUMAN) VSDAFHK.A antithrombin-III P01008 R.EVPLNTIIF 0.61precursor (ANT3_ MGR.V HUMAN) antithrombin-III P01008 R.FATTFYQHL 0.66precursor (ANT3_ ADSKNDNDNIF HUMAN) LSPLSISTAFA MTK.L antithrombin-IIIP01008 R.ITDVIPSE 0.60 precursor (ANT3_ AINELTVL HUMAN) VLVNTIYFK.Gantithrombin-III P01008 R.RVWELSK.A 0.63 precursor (ANT3_ HUMAN)antithrombin-III P01008 R.VAEGTQVLELP 0.62 precursor (ANT3_FKGDDITM*VLIL HUMAN) PKPEK.S antithrombin-III P01008 R.VAEGTQVLELP 0.62precursor (ANT3_ FKGDDITMVLILP HUMAN) KPEK.S apolipoprotein A-II P02652K.AGTELVNFLSY 0.61 preproprotein (APOA2_ FVELGTQPATQ.- HUMAN)apolipoprotein A-II P02652 K.EPCVESLVSQY 0.63 preproprotein (APOA2_FQTVTDYGK.D HUMAN) apolipoprotein A-IV P06727 K. ALVQQMEQLR.Q 0.61precursor (APOA4_ HUMAN) apolipoprotein A-IV P06727 K.LGPHAGDVEGH 0.61precursor (APOA4_ LSFLEK.D HUMAN) apolipoprotein A-IV P06727K.SELTQQLNAL 0.71 precursor (APOA4_ FQDK.L HUMAN) apolipoprotein A-IVP06727 K.SLAELGGHLD 0.61 precursor (APOA4_ QQVEEFRR.R HUMAN)apolipoprotein A-IV P06727 K.VKIDQTVEEL 0.75 precursor (APOA4_ RR.SHUMAN) apolipoprotein A-IV P06727 K.VNSFFSTFK.E 0.63 precursor (APOA4_HUMAN) apolipoprotein P04114 K.ATFQTPDFIVP 0.65 B-100 (APOB_ LTDLR.Iprecursor HUMAN) apolipoprotein P04114 K.AVSM*PSFSIL 0.65 B-100 (APOB_GSDVR.V precursor HUMAN) apolipoprotein P04114 K.AVSMPSFSILG 0.67 B-100(APOB_ SDVR.V precursor HUMAN) apolipoprotein P04114 K.EQHLFLPFSY 0.65B-100 (APOB_ K.N precursor HUMAN) apolipoprotein P04114 K.KIISDYHQQF0.63 B-100 (APOB_ R.Y precursor HUMAN) apolipoprotein P04114K.QVFLYPEKDEPT 0.64 B-100 (APOB_ YILNIK.R precursor HUMAN)apolipoprotein P04114 K.SPAFTDLHLR.Y 0.69 B-100 (APOB_ precursor HUMAN)apolipoprotein P04114 K.TILGTMPAFEVS 0.62 B-100 (APOB_ LQALQK.Aprecursor HUMAN) apolipoprotein P04114 K.VLADKFIIPGL 0.72 B-100 (APOB_K.L precursor HUMAN) apolipoprotein P04114 K.YSQPEDSLIPFF 0.61 B-100(APOB_ EITVPESQLTVSQF precursor HUMAN) TLPK.S apolipoprotein P04114R.DLKVEDIPLA 0.64 B-100 (APOB_ R.I precursor HUMAN) apolipoproteinP04114 R.GIISALLVPPE 0.81 B-100 (APOB_ TEEAK.Q precursor HUMAN)apolipoprotein P04114 R.ILGEELGFASL 0.62 B-100 (APOB_ HDLQLLGK.Lprecursor HUMAN) apolipoprotein P04114 R.LELELRPTGEI 0.60 B-100 (APOB_EQYSVSATYELQ precursor HUMAN) R.E apolipoprotein P04114 R.NIQEYLSILT0.68 B-100 (APOB_ DPDGK.G precursor HUMAN) apolipoprotein P04114R.TFQIPGYTVPV 0.75 B-100 (APOB_ VNVEVSPFTIEMS precursor HUMAN)AFGYVFPK.A apolipoprotein P04114 R.TIDQMLNSELQ 0.70 B-100 (APOB_WPVPDIYLR.D precursor HUMAN) apolipoprotein P02654 K.MREWFSETFQ 0.61 C-I(APOC1_ K.V precursor HUMAN) apolipoprotein P02655 K.STAAMSTYTGI 0.61C-II (APOC2_ FTDQVLSVLKGE precursor HUMAN) E.- apolipoprotein P02656R.GWVTDGFSSL 0.62 C-III (APOC3_ K.D precursor HUMAN) apolipoproteinP02649 R.AATVGSLAGQP 0.61 E (APOE_ LQER.A precursor HUMAN)apolipoprotein P02649 R.LKSWFEPLVED 0.65 E (APOE_ MQR.Q precursor HUMAN)apolipoprotein P02649 R.WVQTLSEQVQE 0.64 E (APOE_ ELLSSQVTQELR.Aprecursor HUMAN) ATP-binding O14678 K.LCGGGRWELM* 0.60 cassette (ABCD4_R.I sub-family HUMAN) D member 4 ATP-binding Q9NUQ8 K.LPGLLK.R 0.73cassette (ABCF3_ sub-family HUMAN) F member 3 beta-2- P02749K.EHSSLAFWK.T 0.64 glycoprotein 1 (APOH_ precursor HUMAN) beta-2- P02749R.TCPKPDDLPFS 0.60 glycoprotein (APOH_ TVVPLK.T 1 HUMAN) precursorbeta-2- P02749 R.VCPFAGILENG 0.68 glycoprotein (APOH_ AVR.Y 1 HUMAN)precursor beta-Ala-Flis Q96KN2 K.LFAAFFLEMAQ 0.68 dipeptidase (CNDP1_LH.- precursor HUMAN) biotinidase P43251 K.SHLIIAQVAK. 0.62 precursor(BTD_ N HUMAN) carboxypeptidase Q96IY4 K.NAIWIDCGIHA 0.62 B2 (CBPB2_ R.Epreproprotein HUMAN) carboxypeptidase P15169 R.EALIQFLEQVH 0.69 N (CBPN_QGIK.G catalytic HUMAN) chain precursor carboxypeptidase N P22792R.LLNIQTYCAGP 0.62 subunit 2 (CPN2_ AYLK.G precursor HUMAN) catalaseP04040 R.LCENIAGHLKD 0.62 (CATA_ AQIFIQK.K HUMAN) ceruloplasmin P00450K.AETGDKVYVHL 0.61 precursor (CERU_ K.N HUMAN) ceruloplasmin P00450K.AGLQAFFQVQE 0.62 precursor (CERU_ CNK.S HUMAN) ceruloplasmin P00450K.DIASGLIGPLI 0.63 precursor (CERU_ ICK.K HUMAN) ceruloplasmin P00450K.DIFTGLIGPM* 0.63 precursor (CERU_ K.I HUMAN) ceruloplasmin P00450K.DIFTGLIGPM 0.68 precursor (CERU_ K.I HUMAN) ceruloplasmin P00450K.M*YYSAVDPTK 0.62 precursor (CERU_ DIFTGLIGPMK.I HUMAN) ceruloplasminP00450 K.MYYSAVDPTKD 0.63 precursor (CERU_ IFTGLIGPM*K.I HUMAN)ceruloplasmin P00450 K.PVWLGFLGPII 0.63 precursor (CERU_ K.A HUMAN)ceruloplasmin P00450 R.ADDKVYPGEQY 0.64 precursor (CERU_ TYMLLATEEQSPGHUMAN) EGDGNCVTR.I ceruloplasmin P00450 R.DTANLFPQTSL 0.71 precursor(CERU_ TLHM*WPDTEGTF HUMAN) NVECLTTDHYTGG MK.Q ceruloplasmin P00450R.DTANLFPQTSL 0.68 precursor (CERU_ TLHMWPDTEGTFN HUMAN) VECLTTDHYTGGMK.Q ceruloplasmin P00450 R.FNKNNEGTYYS 0.74 precursor (CERU_ PNYNPQSR.SHUMAN) ceruloplasmin P00450 R.IDTINLFPATL 0.75 precursor (CERU_FDAYM*VAQNPGE HUMAN) WM*LSCQNLNHLK .A ceruloplasmin P00450 R.IDTINLFPATL0.86 precursor (CERU_ FDAYM*VAQNPGE HUMAN) WMLSCQNLNHLK. A ceruloplasminP00450 R.IDTINLFPATL 0.60 precursor (CERU_ FDAYMVAQNPGEW HUMAN)M*LSCQNLNHLK. A ceruloplasmin P00450 R.KAEEEHLGILG 0.71 precursor (CERU_PQLHADVGDKVK. HUMAN) I ceruloplasmin P00450 R.TTIEKPVWLGF 0.63 precursor(CERU_ LGPIIK.A HUMAN) cholinesterase P06276 R.FWTSFFPK.V 0.76 precursor(CHLE_ HUMAN) clusterin P10909 K.LFDSDPITVTV 0.78 preproprotein (CLUS_PVEVSR.K HUMAN) clusterin P10909 R.ASSIIDELFQD 0.68 preproprotein (CLUS_R.F HUMAN) coagulation P00740 K.WIVTAAHCVET 0.60 factor (FA9_ GVK.I IXHUMAN) preproprotein coagulation P08709 R.FSLVSGWGQLL 0.78 factor (FA7_DR.G VII HUMAN) isoform a preproprotein coagulation P00742 K.ETYDFDIAVLR0.75 factor (FA10_ .L X HUMAN) preproprotein coiled-coil Q8IYE1K.VRQLEMEIGQ. 0.67 domain- (CCD13_ LNVHYLR.N containing HUMAN) protein13 complement P02745 R.PAFSAIR.R 0.66 C1q (C1QA_ subcomponent HUMAN)subunit A precursor complement P02746 K.VVTFCDYAYNT 0.63 C1q (C1QB_FQVTTGGMVLK.L subcomponent HUMAN) subunit B precursor complement P02747K.FQSVFTVTR.Q 0.63 C1q (C1QC_ subcomponent HUMAN) subunit C precursorcomplement P00736 K.TLDEFTIIQNL 0.62 C1r (C1R_ QPQYQFR.D subcomponentHUMAN) precursor complement P00736 R.MDVFSQNMFCA 0.68 C1r (C1R_ GHPSLK.Qsubcomponent HUMAN) precursor complement P00736 R.WILTAAHTLYP 0.74 C1r(C1R_ K.E subcomponent HUMAN) precursor complement C1s P09871K.FYAAGLVSWGP 0.68 subcomponent (C1S_ Q.CGTYGLYTR.V precursor HUMAN)complement C1s P09871 K.GFQVVVTLR.R 0.63 subcomponent (C1S_ precursorHUMAN) complement C2 P06681 R.GALISDQWVLT 0.61 isoform 3 (CO2_ AAHCFR.DHUMAN) complement C2 P06681 R.PICLPCTMEAN 0.66 isoform 3 (CO2_ LALR.RHUMAN) complement C3 P01024 R.YYGGGYGSTQA 0.75 precursor (CO3_TFMVFQALAQYQK HUMAN) .D complement C4-A P0COL4 K.GLCVATPVQLR 0.74isoform 1 (CO4A_ .V HUMAN) complement C4-A P0COL4 K.M*RPSTDTITV 0.83isoform 1 (CO4A_ M*VENSHGLR.V HUMAN) complement C4-A P0COL4K.MRPSTDTITVM 0.72 isoform 1 (CO4A_ *VENSHGLR.V HUMAN) complement C4-AP0COL4 K.VGLSGM*AIAD 0.71 isoform 1 (CO4A_ VTLLSGFHALR.A HUMAN)complement C4-A P0COL4 K.VLSLAQEQVGG 0.63 isoform 1 (CO4A_ SPEK.L HUMAN)complement C4-A P0COL4 R.EMSGSPASGIP 0.65 isoform 1 (CO4A_ VK.V HUMAN)complement C4-A P0COL4 R.GCGEQTM*IYL 0.75 isoform 1 (CO4A_ APTLAASR.YHUMAN) complement C4-A P0COL4 R.GLQDEDGYR.M 0.75 isoform 1 (CO4A_ HUMAN)complement C4-A P0COL4 R.GQIVFMNREP 0.93 isoform 1 (CO4A_ K.R HUMAN)complement C4-A P0COL4 R.KKEVYM*PSSI 0.72 isoform 1 (CO4A_ FQDDFVIPDISEPHUMAN) GTWK.I complement C4-A P0COL4 R.LPMSVR.R 0.78 isoform 1 (CO4A_HUMAN) complement C4-A P0COL4 R.LTVAAPPSGGP 0.84 isoform 1 (CO4A_GFLSIER.P HUMAN) complement C4-A P0COL4 R.NFLVR.A 0.75 isoform 1 (CO4A_HUMAN) complement C4-A P0COL4 R.NGESVKLHLET 0.88 isoform 1 (CO4A_DSLALVALGALDT HUMAN) ALYAAGSK.S complement C4-A P0COL4 R.QGSFQ.GGFR.0.60 isoform 1 (CO4A_ S HUMAN) complement C4-A P0COL4 R.TLEIPGNSDPN 0.69isoform 1 (CO4A_ MIPDGDFNSYVR. HUMAN) V complement C4-A P0COL4R.VTASDPLDTLG 0.63 isoform 1 (CO4A_ SEGALSPGGVASL HUMAN) LR.Lcomplement C4-A P0COL4 R.YLDKTEQWSTL 0.67 isoform 1 (CO4A_ PPETK.DHUMAN) complement C5 P01031 K.ADNFLLENTLP 0.63 preproprotein (CO5_AQSTFTLAISAYA HUMAN) LSLGDK.T complement C5 P01031 K.ALVEGVDQLFT 0.63preproprotein (CO5_ DYQIK.D HUMAN) complement C5 P01031 K.DGHVILQLNSI0.62 preproprotein (CO5_ PSSDFLCVR.F HUMAN) complement C5 P01031K.DVFLEMNIPYS 0.63 preproprotein (CO5_ VVR.G HUMAN) complement C5 P01031K.EFPYRIPLDLV 0.60 preproprotein (CO5_ PK.T HUMAN) complement C5 P01031K.FQNSAILTIQP 0.67 preproprotein (CO5_ K.Q HUMAN) complement C5 P01031K.VFKDVFLEMNI 0.63 preproprotein (CO5_ PYSVVR.G HUMAN) complement C5P01031 R.VFQFLEK.S 0.61 preproprotein (CO5_ HUMAN) complement P13671K.DLHLSDVFLK. 0.60 component C6 (CO6_ A precursor HUMAN) complementP13671 R.TECIKPVVQEV 0.62 component C6 (CO6_ LTITPFQR.L precursor HUMAN)complement P10643 K.SSGWHFVVK.F 0.61 component C7 (CO7_ precursor HUMAN)complement P10643 R.ILPLTVCK.M 0.75 component C7 (CO7_ precursor HUMAN)complement P07357 R.ALDQYLMEFNA 0.65 component (CO8A_ CR.C C8 alphaHUMAN) chain precursor complement P07360 K.YGFCEAADQFH 0.60 component C8(CO8G_ VLDEVR.R gamma chain HUMAN) precursor complement P02748R.AIEDYINEFSV 0.69 component C9 (CO9_ RK.C precursor HUMAN) complementP02748 R.TAGYGINILGM 0.69 component C9 (CO9_ DPLSTPFDNEFYN precursorHUMAN) GLCNR.D complement P00751 K.ALFVSEEEKK. 0.64 factor B (CFAB_ Lpreproprotein HUMAN) complement P00751 K.CLVNLIEK.V 0.70 factor B (CFAB_HUMAN) preproprotein complement P00751 K.EAGIPEFYDYD 0.66 factor B(CFAB_ VALIK.L preproprotein HUMAN) complement P00751 K.VSEADSSNADW 0.73factor B (CFAB_ VTK.Q preproprotein HUMAN) complement P00751K.YGQTIRPICLP 0.67 factor B (CFAB_ CTEGTTR.A preproprotein HUMAN)complement P00751 R.DLEIEVVLFHP 0.71 factor B (CFAB_ NYNINGK.Kpreproprotein HUMAN) complement P00751 R.FLCTGGVSPYA 0.64 factor B(CFAB_ DPNTCR.G preproprotein HUMAN) complement P08603 K.DGWSAQPTCI 0.80factor H (CFAH_ K.S isoform a HUMAN) precursor complement P08603K.EGWIHTVCING 0.67 factor H (CFAH_ R.W isoform a HUMAN) precursorcomplement P08603 K.TDCLSLPSFEN 0.61 factor H (CFAH_ AIPMGEK.K isoform aHUMAN) precursor complement P08603 R.DTSCVNPPTVQ 0.60 factor H (CFAH_NAYIVSR.Q isoform a HUMAN) precursor complement P08603 K.CTSTGWIPAP 0.68factor H (CFAH_ R.C isoform b HUMAN) precursor complement P08603K.IIYKENER.F 0.76 factor H (CFAH_ isoform b HUMAN) precursor complementP08603 K.IVSSAM*EPDR 0.75 factor H (CFAH_ EYHFGQAVR.F isoform b HUMAN)precursor complement P08603 K.IVSSAMEPDRE 0.68 factor H (CFAH_YHFGQAVR.F isoform b HUMAN) precursor complement P08603 R.CTLKPCDYPDI0.81 factor H (CFAH_ K.H isoform b HUMAN) precursor complement P08603R.KGEWVALNPL 0.60 factor H (CFAH_ R.K isoform b HUMAN) precursorcomplement P08603 R.KGEWVALNPLR 0.69 factor H (CFAH_ K.C isoform bHUMAN) precursor complement P08603 R.RPYFPVAVGK. 0.68 factor H (CFAH_ Yisoform b HUMAN) precursor complement Q03591 R.EIMENYNIAL 0.64 factor(FHR1_ R.W H-related HUMAN) protein 1 precursor complement P05156K.DASGITCGGIY 0.71 factor 1 (CFAI_ IGGCWILTAAHCL preproprotein HUMAN)R.A complement P05156 K.VANYFDWISYH 0.72 factor 1 (CFAI_ VGR.Ppreproprotein HUMAN) complement P05156 R.IIFHENYNAGT 0.63 factor 1(CFAI_ YQNDIALIEMK.K preproprotein HUMAN) complement P05156R.YQIWTTVVDWI 0.63 factor 1 (CFAI_ HPDLK.R preproprotein HUMAN)conserved Q9Y2V7 K.ISNLLK.F 0.65 oligomeric (COG6_ Golgi complex HUMAN)subunit 6 isoform corticosteroid- P08185 R.WSAGLTSSQVD 0.62 binding(CBG_ LYIPK.V globulin HUMAN) precursor C-reactive P02741 K.YEVQGEVFTKP0.60 protein (CRP_ QLWP.- precursor HUMAN) dopamine P09172 R.HVLAAWALG0.88 beta- (DOPO_ AK.A hydroxylase HUMAN) precursor double- Q9INS39R.AGLRYVCLAEP 0.75 stranded (RED2_ AER.R RNA-specific HUMAN) editase B2dual Q9NRD8 R.FTQLCVKGGGG 0.65 oxidase 2 (DUOX2_ GGNGIR.D precursorHUMAN) FERM domain- Q9BZ67 R.VQLGPYQPGRP 0.65 containing (FRMD8_AACDLR.E protein 8 HUMAN) fetuin-B Q9UGM5 R.GGLGSLFYLTL 0.83 precursor(FETUB_ DVLETDCHVLR.K HUMAN) ficolin-3 075636 R.ELLSQGATLSG 0.69isoform 1 (FCN3_ WYHLCLPEGR.A precursor HUMAN) gastric P27352K.KTTDM*ILNEI 0.60 intrinsic (IF_ KQGK.F factor HUMAN) precursorgelsolin P06396 K.NWRDPDQTDGL 0.72 isoform d (GELS_ GLSYLSSHIANVE HUMAN)R.V gelsolin P06396 K.TPSAAYLWVGT 0.80 isoform d (GELS_ GASEAEK.T HUMAN)gelsolin P06396 R.VEKFDLVPVPT 0.60 isoform d (GELS_ NLYGDFFTGDAYV HUMAN)ILK.T gelsolin P06396 R.VPFDAATLHT 0.67 isoform d (GELS_ STAM AAQHGM DHUMAN) DDGTGQK.Q glutathione P22352 K.FYTFLK.N 0.63 peroxidase 3 (GPX3_precursor HUMAN) hemopexin P02790 K.GDKVWVYPPEK 0.65 precursor (HEMO_K.E HUMAN) hemopexin P02790 K.LLQDEFPGIPS 0.71 precursor (HEMO_PLDAAVECHR.G HUMAN) hemopexin P02790 K.SGAQATWTELP 0.64 precursor (HEMO_WPHEK.V HUMAN) hemopexin P02790 K.SGAQATWTELP 0.61 precursor (HEMO_WPHEKVDGALCME HUMAN) K.S hemopexin P02790 K.VDGALCMEK.S 0.66 precursor(HEMO_ HUMAN) hemopexin P02790 R.DYFMPCPGR.G 0.68 precursor (HEMO_HUMAN) hemopexin P02790 R.EWFWDLATGTM 0.64 precursor (HEMO_ *K.E HUMAN)hemopexin P02790 R.QGHNSVFLIK. 0.71 precursor (HEMO_ G HUMAN) heparinP05546 K.HQGTITVN E 0.60 cofactor 2 (HEP2_ EGTQATTVTTVG precursor HUMAN)FMPLSTQVR.F heparin P05546 K.YEITTIHNLF 0.62 cofactor 2 (HEP2_ R.Kprecursor HUMAN) heparin cofactor 2 P05546 R.LNILNAK.F 0.68 precursor(HEP2_ HUMAN) heparin cofactor 2 P05546 R.NFGYTLR.S 0.64 precursor(HEP2_ HUMAN) heparin cofactor 2 P05546 R.VLKDQVNTFDN 0.63 precursor(HEP2_ IFIAPVGISTAMG HUMAN) M*ISLGLK.G hepatocyte cell Q14CZ8K.PLLNDSRMLLS 0.61 adhesion molecule (HECAM_ PDQK.V precursor HUMAN)hepatocyte growth Q04756 R.VQLSPDLLATL 0.82 factor activator (HGFA_PEPASPGR.Q preproprotein HUMAN) histidine-rich P04196 R.DGYLFQLLR.I 0.63glycoprotein (HRG_ precursor HUMAN) hyaluronan-binding Q14520 K.FLNWIK.A0.82 protein 2 isoform 1 (HABP2_ preproprotein HUMAN) hyaluronan-bindingQ14520 K.LKPVDGHCALE 0.61 protein 2 isoform 1 (HABP2_ SK.Y preproproteinHUMAN) hyaluronan-binding Q14520 K.RPGVYTQVTK. 0.74 protein 2 isoform 1(HABP2_ F preproprotein HUMAN) inactive caspase-12 Q6UXS9 K.AGADTHGRLLQ0.74 (CASPC_ GNICNDAVTK.A HUMAN) insulin-degrading P14735 K.KIIEKM*ATFE0.85 enzyme isoform 1 (IDE_ IDEK.R HUMAN) insulin-like growth P35858R.SFEGLGQLEVL 0.62 factor-binding (ALS_ TLDHNQ.LQEVK. protein HUMAN) Acomplex acid labile subunit isoform 2 precursor inter-alpha- P19827K.ELAAQTIKK.S 0.81 trypsin (ITIH1_ inhibitor HUMAN) heavy chainHI isoform a precursor inter-alpha-trypsin P19827 K.GSLVQASEANL 0.71inhibitor heavy chain (IT1H1__ QAAQDFVR.G HI isoform a HUMAN) precursorinter-alpha-trypsin P19827 K.QLVHHFEIDVD 0.70 inhibitor heavy chain(ITIH1_ IFEPQGISK.L HI isoform a HUMAN) precursor inter-alpha- P19827K.QYYEGSEIVVA 0.83 trypsin (ITIH1_ GR.I inhibitor HUMAN) heavy chainheparin cofactor 2 P05546 R.LNILNAK.F 0.68 precursor (HEP2_ HUMAN)heparin cofactor 2 P05546 R.NFGYTLR.S 0.64 precursor (HEP2_ HUMAN)heparin cofactor 2 P05546 R.VLKDQVNTFDN 0.63 precursor (HEP2_IFIAPVGISTAMG HUMAN) M*ISLGLK.G hepatocyte cell Q14CZ8 K.PLLNDSRMLLS0.61 adhesion molecule (HECAM_ PDQK.V precursor HUMAN) hepatocyte growthQ04756 R.VQLSPDLLATL 0.82 factor activator (HGFA_ PEPASPGR.Qpreproprotein HUMAN) histidine-rich P04196 R.DGYLFQLLR.I 0.63glycoprotein (HRG_ precursor HUMAN) hyaluronan-binding Q14520 K.FLNWIK.A0.82 protein 2 isoform 1 (HABP2_ preproprotein HUMAN) hyaluronan-bindingQ14520 K.LKPVDGHCALE 0.61 protein 2 isoform 1 (HABP2_ SK.Y preproproteinHUMAN) hyaluronan-binding Q14520 K.RPGVYTQVTK. 0.74 protein 2 isoform 1(HABP2_ F preproprotein HUMAN) inactive caspase-12 Q6UXS9 K.AGADTHGRLLQ0.74 (CASPC_ GNICNDAVTK.A HUMAN) insulin-degrading P14735 K.KIIEKM*ATFE0.85 enzyme isoform 1 (IDE_ IDEK.R HUMAN) insulin-like P35858R.SFEGLGQLEVL 0.62 growth (ALS_ TLDHNQ.LQEVK. factor-binding HUMAN) Aprotein complex acid labile subunit isoform 2 precursor inter-alpha-P19827 K.ELAAQTIKK.S 0.81 trypsin (ITIH1_ inhibitor HUMAN) heavy chainHI isoform a precursor inter-alpha- P19827 K.GSLVQASEANL 0.71 trypsin(ITIH1_ QAAQDFVR.G inhibitor HUMAN) heavy chain HI isoform a precursorinter-alpha- P19827 K.QLVHHFEIDVD 0.70 trypsin (ITIH1_ IFEPQGISK.Linhibitor HUMAN) heavy chain HI isoform a precursor inter-alpha- P19827K.QYYEGSEIVVA 0.83 trypsin (ITIH1_ GR.I inhibitor HUMAN) heavy chainH1 isoform a precursor inter-alpha-trypsin P19827 R.EVAFDLEIPKT 0.70inhibitor heavy chain (ITIH1_ AFISDFAVTADGN HI isoform a HUMAN)AFIGDIK.D precursor inter-alpha-trypsin P19827 R.GMADQDGLKPT 0.63inhibitor heavy chain (ITIH1_ IDKPSEDSPPLEM HI isoform a HUMAN) *LGPR.Rprecursor inter-alpha-trypsin P19827 R.GMADQDGLKPT 0.60inhibitor heavy chain (ITIH1_ IDKPSEDSPPLEM HI isoform a HUMAN) LGPR.Rprecursor inter-alpha-trypsin P19823 K.FDPAKLDQIES 0.80inhibitor heavy chain (ITIH2_ VITATSANTQLVL H2 precursor HUMAN)ETLAQM*DDLQDF LSK.D inter-alpha-trypsin P19823 K.KFYNQVSTPLL 0.76inhibitor heavy chain (ITIH2_ R.N H2 precursor HUMAN)inter-alpha-trypsin P19823 K.NILFVIDVSGS 0.68 inhibitor heavy chain(ITIH2_ M*WGVK.M H2 precursor HUMAN) inter-alpha-trypsin P19823K.NILFVIDVSGS 0.62 inhibitor heavy chain (ITIH2_ MWGVK.M H2 precursorHUMAN) inter-alpha-trypsin P19823 R.KLGSYEHR.I 0.72inhibitor heavy chain (ITIH2_ H2 precursor HUMAN) inter-alpha-trypsinP19823 R.LSNENHGIAQ 0.66 inhibitor heavy chain (ITIH2_ R.I H2 precursorHUMAN) inter-alpha-trypsin P19823 R.MATTMIQSK.V 0.60inhibitor heavy chain (ITIH2_ H2 precursor HUMAN) inter-alpha-trypsinP19823 R.SILQ.M*SLDH 0.63 inhibitor heavy chain (ITIH2_ HIVTPLTSLVIENH2 precursor HUMAN) EAGDER.M inter-alpha-trypsin P19823 R.SILQMSLDHHI0.65 inhibitor heavy chain (ITIH2_ VTPLTSLVIENEA H2 precursor HUMAN)GDER.M inter-alpha-trypsin P19823 R.TEVNVLPGAK. 0.69inhibitor heavy chain (ITIH2_ V H2 precursor HUMAN) inter-alpha-trypsinQ14624 K.NWFVIDK.S 0.68 inhibitor heavy chain (ITIH4_ H4 isoform 1HUMAN) precursor inter-alpha-trypsin Q14624 K.WKETLFSVMPG 0.65inhibitor heavy chain (ITIH4_ LK.M H4 isoform 1 HUMAN) precursorinter-alpha-trypsin Q14624 K.YIFHNFM*ER. 0.67 inhibitor heavy chain(ITIH4_ L H4 isoform 1 HUMAN) precursor inter-alpha-trypsin Q14624R.FAHTVVTSR.V 0.63 inhibitor heavy chain (ITIH4_ H4 isoform 1 HUMAN)precursor inter-alpha-trypsin Q14624 R.FKPTLSQQQK. 0.60inhibitor heavy chain (ITIH4_ S H4 isoform 1 HUMAN) precursorinter-alpha-trypsin Q14624 R.IHEDSDSALQL 0.64 inhibitor heavy chain(ITIH4_ QDFYQEVANPLLT H4 isoform 1 HUMAN) AVTFEYPSNAVEE precursorVTQNNFR.L inter-alpha-trypsin Q14624 R.MNFRPGVLSS 0.63inhibitor heavy chain (ITIH4_ R.Q H4 isoform 1 HUMAN) precursorinter-alpha-trypsin Q14624 R.NVHSAGAAGS 0.62 inhibitor heavy chain(ITIH4_ R.M H4 isoform 1 HUMAN) precursor inter-alpha-trypsin Q14624R.NVHSGSTFFK. 0.75 inhibitor heavy chain (IT1H4_ Y H4 isoform 1 HUMAN)precursor inter-alpha-trypsin Q14624 R.RLGVYELLLK. 0.66inhibitor heavy chain (ITIH4_ V H4 isoform 1 HUMAN) precursorkallistatin P29622 K.KLELHLPK.F 0.78 precursor (KAIN_ HUMAN) kallistatinP29622 R.EIEEVLTPEML 0.60 precursor (KAIN_ MR.W HUMAN)kininogen-1 isoform 2 P01042 K.AATGECTATVG 0.67 precursor (KNG1_ KR.SHUMAN) kininogen-1 isoform 2 P01042 K.LGQSLDCNAEV 0.72 precursor (KNG1_YWPWEK.K HUMAN) kininogen-1 isoform 2 P01042 K.YNSQNQSNNQF 0.62precursor (KNG1_ VLYR.I HUMAN) kininogen-1 isoform 2 P01042R.QVVAGLNFR.I 0.64 precursor (KNG1_ HUMAN) leucine-rich alpha-2- P02750K.DLLLPQPDLR. 0.64 glycoprotein (A2GL_ Y precursor HUMAN)leucine-rich alpha-2- P02750 R.LHLEGNKLQVL 0.76 glycoprotein (A2GL_ GK.Dprecursor HUMAN) leucine-rich alpha-2- P02750 R.TLDLGENQLET 0.61glycoprotein (A2GL_ LPPDLLR.G precursor HUMAN) lipopolysaccharide-P18428 K.GLQYAAQEGLL 0.82 binding protein (LBP_ ALQSELLR.I precursorHUMAN) lipopolysaccharide- P18428 K.LAEGFPLPLL 0.66 binding protein(LBP_ K.R precursor HUMAN) lumican precursor P51884 K.SLEYLDLSFN 0.65(LUM_ Q.IAR.L HUMAN) lumican precursor P51884 R.LKEDAVSAAF 0.74 (LUM_K.G HUMAN) m7GpppX Q96C86 R.IVFENPDPSDG 0.62 diphosphatase (DCPS_FVLIPDLK.W HUMAN) matrix Q99542 R.VYFFK.G 0.63 metalloproteinase-19(MMP19_ isoform 1 HUMAN) preproprotein MBT domain- Q05BQ5 K.WFDYLR.E0.65 containing protein 1 (MBTD1_ HUMAN) monocyte P08571 R.LTVGAAQVPAQ0.66 differentiation (CD14_ LLVGALR.V antigen CD14 HUMAN) precursorpappalysin-1 Q13219 R.VSFSSPLVAIS 0.66 preproprotein (PAPP1_ GVALR.SHUMAN) phosphatidylinositol- P80108 K.GIVAAFYSGPS 0.71 glycan-specific(PHLD_ LSDKEK.L phospholipase D HUMAN) precursor phosphatidylinositol-P80108 R.WYVPVKDLLGI 0.71 glycan-specific (PHLD_ YEK.L phospholipase DHUMAN) precursor pigment epithelium- P36955 K.LQSLFDSPDFS 0.61derived factor (PEDF_ K.I precursor HUMAN) pigment epithelium- P36955R.ALYYDLISSPD 0.72 derived factor (PEDF_ IHGTYK.E precursor HUMAN)plasma kallikrein P03952 R.CLLFSFLPASS 0.60 preproprotein (KLKB1_INDMEKR.F HUMAN) plasma protease Cl P05155 K.FQPTLLTLPR. 0.70inhibitor precursor (IC1_ I HUMAN) plasma protease Cl P05155K.GVTSVSQ.IFH 0.66 inhibitor precursor (IC1_ SPDLAIR.D HUMAN)plasminogen isoform P00747 K.VIPACLPSPNY 0.63 1 precursor (PLMN_ VVADR.THUMAN) plasminogen isoform P00747 R.FVTWIEGVMR. 0.60 1 precursor (PLMN_N HUMAN) plasminogen isoform P00747 R.HSIFTPETNP 0.63 1 precursor (PLMN_R.A HUMAN) platelet basic P02775 K.GKEESLDSDLY 0.70 protein (CXCL7_AELR.C preproprotein HUMAN) platelet P40197 K.MVLLEQLFLDH 0.66glycoprotein (GPV_ NALR.G V precursor HUMAN) platelet P40197R.LVSLDSGLLNS 0.88 glycoprotein (GPV_ LGALTELQFHR.N V precursor HUMAN)pregnancy zone P20742 K.ALLAYAFSLLG 0.66 protein precursor (PZP_ K.QHUMAN) pregnancy zone P20742 K.DLFHCVSFTLP 0.86 protein precursor (PZP_R.I HUMAN) pregnancy zone P20742 K.MLQ.ITNTGFE 0.84 protein precursor(PZP_ MK.L HUMAN) pregnancy zone P20742 R.NELIPLIYLEN 0.65protein precursor (PZP_ PRR.N HUMAN) pregnancy zone P20742 R.SYIFIDEAHIT0.68 protein precursor (PZP_ QSLTWLSQMQK.D HUMAN) pregnancy-specificP11465 R.SDPVTLNLLHG 0.66 beta-l-glycoprotein 2 (PSG2_ PDLPR.I precursorHUMAN) pregnancy-specific Q16557 R.TLFLFGVTK.Y 0.62beta-l-glycoprotein 3 (PSG3_ precursor HUMAN) pregnancy-specific Q15238R.ILILPSVTR.N 0.76 beta-l-glycoprotein 5 (PSG5_ precursor HUMAN)pregnancy-specific Q00889 R.SDPVTLNLLP 0.63 beta-l-glycoprotein 6 (PSG6_K.L isoform a HUMAN) progesterone- Q8WXW3 R.VLQLEK.Q 0.71induced-blocking (PIBF1_ factor 1 HUMAN) protein AMBP P02760R.VVAQGVGIPED 0.60 preproprotein (AMBP_ SIFTMADR.G HUMAN)protein CBFA2T2 043439 R.LTEREWADEWK 0.70 isoform MTGRlb (MTG8R _HLDHALNCIMEMV HUMAN) EK.T protein FAM98C Q17RN3 R.ALCGGDGAAAL 0.75(FA98C_ REPGAGLR.L HUMAN) protein NLRC3 Q7RTR2 K.ALM*DLLAGKG 0.92(NLRC3_ SQGSQAPQALDR. HUMAN) T protein Z-dependent Q9UK55 K.MGDHLALEDYL0.60 protease inhibitor (ZPI_ TTDLVETWLR.N precursor HUMAN) prothrombinP00734 K.SPQELLCGASL 0.84 preproprotein (THRB_ ISDR.W HUMAN) prothrombinP00734 R.LAVTTHGLPCL 0.62 preproprotein (THRB_ AWASAQAK.A HUMAN)prothrombin P00734 R.SEGSSVNLSPP 0.70 preproprotein (THRB_ LEQCVPDR.GHUMAN) prothrombin P00734 R.SGIECQLWR.S 0.68 preproprotein (THRB_ HUMAN)prothrombin P00734 R.TATSEYQTFFN 0.60 preproprotein (THRB_ PR.T HUMAN)prothrombin P00734 R.VTGWGNLKETW 0.69 preproprotein (THRB_ TANVGK.GHUMAN) putative Q5T013 R.IHLM*AGR.V 0.69 hydroxypyruvate (HYI_isomerase isoform 1 HUMAN) putative Q5T013 R.IHLMAGR.V 0.66hydroxypyruvate (HYI _ isomerase isoform 1 HUMAN) ras-like Q92737R.PAHPALR.L 0.71 protein family (RSLAA_ member 10A HUMAN) precursorras-related GTP- Q7L523 K.ISNIIK.Q 0.82 binding protein A (RRAGA_ HUMAN)retinol-binding P02753 K.M*KYWGVASFL 0.73 protein 4 precursor (RET4_QK.G HUMAN) retinol-binding P02753 R.FSGTWYAM*AK 0.63protein 4 precursor (RET4_ .K HUMAN) retinol-binding P02753R.LLNLDGTCADS 0.79 protein 4 precursor (RET4_ YSFVFSR.D HUMAN)retinol-binding P02753 R.LLNNWDVCADM 0.77 protein 4 precursor (RET4_VGTFTDTEDPAKF HUMAN) K.M sex hormone-binding P04278 R.LFLGALPGEDS 0.66globulin isoform 1 (SHBG _ STSFCLNGLWAQG precursor HUMAN) QR.Lsex hormone-binding P04278 K.DDWFMLGLR.D 0.60 globulin isoform 4 (SHBG _precursor HUMAN) sex hormone-binding P04278 R.SCDVESNPGIF 0.64globulin isoform 4 (SHBG _ LPPGTQAEFNLR. HUMAN) G precursorsex hormone-binding P04278 R.TWDPEGVIFYG 0.65 globulin isoform 4 (SHBG_DTNPKDDWFM*LG precursor HUMAN) LR.D sex hormone-binding P04278R.TWDPEGVIFYG 0.66 globulin isoform 4 (SHBG_ DTNPKDDWFMLGL precursorHUMAN) R.D signal transducer P52630 R.KFCRDIQDPTQ 0.73 and activator of(STAT2_ LAEMIFNLLLEEK transcription 2 HUMAN) .R spectrin beta chain,Q13813 R.NELIRQEKLEQ 0.60 non-erythrocytic 1 (SPTN1_ LAR.R HUMAN)stabilin-1 Q9NY15 R.KNLSER.W 0.88 precursor (STAB1_ HUMAN) succinate-P51649 R.KWYNLMIQNK. 0.88 semialdehyde (SSDH_ D dehydrogenase, HUMAN)mitochondrial tetranectin P05452 K.SRLDTLAQEVA 0.75 precursor (TETN_LLK.E HUMAN) THAP domain- Q8TBB0 K.RLDVNAAGIWE 0.69 containing (THAP6_PKK.G protein HUMAN) thyroxine-binding P05543 R.SILFLGK.V 0.79globulin precursor (THBG_ HUMAN) tripartite motif- Q9C035 R.ELISDLEHRLQ0.60 containing protein 5 (TRIM5_ GSVM*ELLQGVD HUMAN) GVIK.Rvitamin D-binding P02774 K.EDFTSLSLVLY 0.66 protein isoform 1 (VTDB_SR.K precursor HUMAN) vitamin D-binding P02774 K.ELSSFIDKGQE 0.67protein isoform 1 (VTDB_ LCADYSENTFTEY precursor HUMAN) K.Kvitamin D-binding P02774 K.ELSSFIDKGQE 0.66 protein isoform 1 (VTDB_LCADYSENTFTEY precursor HUMAN) KK.K vitamin D-binding P02774K.EVVSLTEACCA 0.65 protein isoform 1 (VTDB_ EGADPDCYDTR.T precursorHUMAN) vitamin D-binding P02774 K.TAMDVFVCTYF 0.84 protein isoform 1(VTDB_ MPAAQLPELPDVE precursor HUMAN) LPTNKDVCDPGNT K.Vvitamin D-binding P02774 R.RTHLPEVFLS 0.69 protein isoform 1 (VTDB_ .KVprecursor HUMAN) vitamin D-binding P02774 R.VCSQYAAYGE 0.66protein isoform 1 (VTDB_ K.K precursor HUMAN) vitronectin precursorP04004 K.LIRDVWGIEGP 0.61 (VTNC_ IDAAFTR.I HUMAN) vitronectin precursorP04004 R.DVWGIEGPIDA 0.63 (VTNC_ AFTR.I HUMAN) vitronectin precursorP04004 R.ERVYFFK.G 0.81 (VTNC_ HUMAN) vitronectin precursor P04004R.FEDGVLDPDYP 0.64 (VTNC_ R.N HUMAN) vitronectin precursor P04004R.IYISGM*APRP 0.75 (VTNC_ SLAK.K HUMAN) zinc finger protein P52746K.TRFLLR.T 0.66 142 (ZN142_ HUMAN)

TABLE 9 Significant peptides (AUC > 0.6) for X!Tandem onlyProtein description Uniprot ID (name) Peptide XT_AUC afamin precursorP43652 K.HELTDEELQSLFTNFANVVDK.C 0.65 (AFAM_HUMAN) afamin precursorP43652 R.NPFVFAPTLLTVAVHFEEVAK.S 0.91 (AFAM_HUMAN) alpha-1- P01011K.ADLSGITGAR.N 0.67 antichymotrypsin (AACT_HUMAN) precursor alpha-1-P01011 K.MEEVEAMLLPETLKR.W 0.60 antichymotrypsin (AACT_HUMAN) precursoralpha-1- P01011 K.WEMPFDPQDTHQSR.F 0.64 antichymotrypsin (AACT_HUMAN)precursor alpha-1- P01011 R.LYGSEAFATDFQDSAAAK.K 0.62 antichymotrypsin(AACT_HUMAN) precursor alpha-1B-glycoprotein P04217 K.HQFLLTGDTQGR.Y0.72 precursor (A1BG_HUMAN) alpha-1B-glycoprotein P04217K.NGVAQEPVHLDSPAIK.H 0.63 precursor (A1BG_HUMAN) alpha-1B-glycoproteinP04217 K.SLPAPWLSM*APVSWITPGLK.T 0.72 precursor (A1BG_HUMAN)alpha-1B-glycoprotein P04217 K.VTLTCVAPLSGVDFQLRR.G 0.67 precursor(A1BG_HUMAN) alpha-1B-glycoprotein P04217 R.C*EGPIPDVTFELLR.E 0.67precursor (A1BG_HUMAN) alpha-1B-glycoprotein P04217 R.C*LAPLEGAR.F 0.79precursor (A1BG_HUMAN) alpha-1B-glycoprotein P04217 R.CLAPLEGAR.F 0.63precursor (A1BG_HUMAN) alpha-1B-glycoprotein P04217 R.GVTFLLR.R 0.69precursor (A1BG_HUMAN) alpha-1B-glycoprotein P04217R.LHDNQNGWSGDSAPVELILSDETL 0.60 precursor (A1BG_HUMAN) PAPEFSPEPESGR.Aalpha-1B-glycoprotein P04217 R.TPGAAANLELIFVGPQHAGNYR.C 0.62 precursor(A1BG_HUMAN) alpha-2-antiplasmin P08697 K.HQM*DLVATLSQLGLQELFQAPDL 0.61isoform a precursor (A2AP_HUMAN) R.G alpha-2-antiplasmin P08697R.LCQDLGPGAFR.L 0.68 isoform a precursor (A2AP_HUMAN)alpha-2-antiplasmin P08697 R.WFLLEQPEIQVAHFPFK.N 0.60isoform a precursor (A2AP_HUMAN) alpha-2-HS-glycoprotein P02765K.VWPQQPSGELFEIEIDTLETTCHVL 0.61 preproprotein (FETUA_HUMAN) DPTPVAR.Calpha-2-HS-glycoprotein P02765 R.HTFMGVVSLGSPSGEVSHPR.K 0.68preproprotein (FETUA_HUMAN) alpha-2-HS-glycoprotein P02765R.Q*PNCDDPETEEAALVAIDYINQNL 0.69 preproprotein (FETUA_HUMAN) PWGYK.Halpha-2-HS-glycoprotein P02765 R.QPNCDDPETEEAALVAIDYINQNLP 0.64preproprotein (FETUA_HUMAN) WGYK.H alpha-2-HS-glycoprotein P02765R.TVVQPSVGAAAGPVVPPCPGR.I 0.64 preproprotein (FETUA_HUMAN)angiotensinogen P01019 K.QPFVQGLALYTPVVLPR.S 0.73 preproprotein(ANGT_HUMAN) angiotensinogen P01019 R.AAM*VGM*LANFLGFR.I 0.62preproprotein (ANGT_HUMAN) apolipoprotein A-IV P06727 K.LVPFATELHER.L0.64 precursor (APOA4_HUMAN) apolipoprotein A-IV P06727 R.LLPHANEVSQK.I0.61 precursor (APOA4_HUMAN) apolipoprotein A-IV P06727R.SLAPYAQDTQEKLNHQLEGLTFQM 0.70 precursor (APOA4_HUMAN) K.Kapolipoprotein B-100 P04114 K.FPEVDVLTK.Y 0.61 precursor (APOB_HUMAN)apolipoprotein B-100 P04114 K.HINIDQFVR.K 0.70 precursor (APOB_HUMAN)apolipoprotein B-100 P04114 K.LLSGGNTLHLVSTTK.T 0.66 precursor(APOB_HUMAN) apolipoprotein B-100 P04114 K.Q*VFLYPEKDEPTYILNIKR.G 0.81precursor (APOB_HUMAN) apolipoprotein B-100 P04114K.QVFLYPEKDEPTYILNIKR.G 0.77 precursor (APOB_HUMAN) apolipoprotein B-100P04114 K.SLHMYANR.L 0.83 precursor (APOB_HUMAN) apolipoprotein B-100P04114 K.SVSDGIAALDLNAVANK.I 0.62 precursor (APOB_HUMAN)apolipoprotein B-100 P04114 K.SVSLPSLDPASAKIEGNLIFDPNNYL 0.67 precursor(APOB_HUMAN) PK.E apolipoprotein B-100 P04114 K.TEVIPPLIENR.Q 0.63precursor (APOB_HUMAN) apolipoprotein B-100 P04114 K.VLVDHFGYTK.D 0.76precursor (APOB_HUMAN) apolipoprotein B-100 P04114R.TSSFALNLPTLPEVKFPEVDVLTK.Y 0.62 precursor (APOB_HUMAN)apolipoprotein C-III P02656 R.GWVTDGFSSLKDYWSTVK.D 0.66 precursor(APOC3_HUMAN) apolipoprotein E P02649 R.GEVQAMLGQSTEELR.V 0.81 precursor(APOE_HUMAN) apolipoprotein E P02649 R.LAVYQAGAR.E 0.63 precursor(APOE_HUMAN) apolipoprotein E P02649 R.LGPLVEQGR.V 0.69 precursor(APOE_HUMAN) attractin isoform 2 O75882 K.LTLTPWVGLR.K 0.69preproprotein (ATRN_HUMAN) beta-2-glycoprotein 1 P02749K.FICPLTGLWPINTLK.C 0.63 precursor (APOH_HUMAN) beta-2-glycoprotein 1P02749 K.TFYEPGEEITYSCKPGYVSR.G 0.62 precursor (APOH_HUMAN) beta-Ala-HisQ96KN2 K.MVVSMTLGLHPWIANIDDTQYLA 0.81 dipeptidase precursor(CNDP1_HUMAN) AK.R beta-Ala-His Q96KN2 K.VFQYIDLHQDEFVQTLK.E 0.65dipeptidase precursor (CNDP1_HUMAN) biotinidase precursor P43251R.TSIYPFLDFM*PSPQVVR.W 0.79 (BTD_HUMAN) carboxypeptidase N P15169R.ELMLQLSEFLCEEFR.N 0.61 catalytic chain (CBPN_HUMAN) precursorceruloplasmin P00450 K.AEEEHLGILGPQLHADVGDKVK.I 0.73 precursor(CERU_HUMAN) ceruloplasmin P00450 K.ALYLQYTDETFR.T 0.64 precursor(CERU_HUMAN) ceruloplasmin P00450 K.DVDKEFYLFPTVFDENESLLLEDN 0.62precursor (CERU_HUMAN) IR.M ceruloplasmin P00450K.HYYIGIIETTWDYASDHGEK.K 0.61 precursor (CERU_HUMAN) ceruloplasminP00450 R.EYTDASFTNRK.E 0.67 precursor (CERU_HUMAN) ceruloplasmin P00450R.HYYIAAEEIIWNYAPSGIDIFTK.E 0.63 precursor (CERU_HUMAN) ceruloplasminP00450 R.IYHSHIDAPK.D 0.62 precursor (CERU_HUMAN) ceruloplasmin P00450R.Q*KDVDKEFYLFPTVFDENESLLLE 0.74 precursor (CERU_HUMAN) DNIR.Mceruloplasmin P00450 R.QKDVDKEFYLFPTVFDENESLLLED 0.65 precursor(CERU_HUMAN) NIR.M ceruloplasmin P00450 R.TYYIAAVEVEWDYSPQR.E 0.90precursor (CERU_HUMAN) coagulation factor IX P00740 R.SALVLQYLR.V 0.69preproprotein (FA9_HUMAN) coagulation factor V P12259 K.EFNPLVIVGLSK.D0.61 precursor (FA5_HUMAN) coagulation factor XII P00748R.NPDNDIRPWCFVLNR.D 0.65 precursor (FA12_HUMAN) coagulation factor XIIP00748 R.VVGGLVALR.G 0.61 precursor (FA12_HUMAN) complement C1q P02746K.NSLLGMEGANSIFSGFLLFPDMEA.- 0.64 subcomponent subunit (C1QB_HUMAN)B precursor complement C1q P02746 K.VPGLYYFTYHASSR.G 0.63subcomponent subunit (C1QB_HUMAN) B precursor complement C1q P02747R.Q*THQPPAPNSLIR.F 0.60 subcomponent subunit (C1QC_HUMAN) C precursorcomplement C1r P00736 R.LPVANPQACENWLR.G 0.72 subcomponent (C1R_HUMAN)precursor complement C2 P06681 K.NQGILEFYGDDIALLK.L 0.74 isoform 3(CO2_HUMAN) complement C2 P06681 K.RNDYLDIYAIGVGK.L 0.61 isoform 3(CO2_HUMAN) complement C2 P06681 R.QPYSYDFPEDVAPALGTSFSHMLG 0.78isoform 3 (CO2_HUMAN) ATNPTQK.T complement C3 P01024 R.IHWESASLLR.S 0.69precursor (CO3_HUMAN) complement C4-A P0C0L4 K.FACYYPR.V 0.64 isoform 1(CO4A_HUMAN) complement C4-A P0C0L4 K.LHLETDSLALVALGALDTALYAAGS 0.74isoform 1 (CO4A_HUMAN) K.S complement C4-A P0C0L4 K.LVNGQSHISLSK.A 0.64isoform 1 (CO4A_HUMAN) complement C4-A P0C0L4 K.M*RPSTDTITVMVENSHGLR.V0.60 isoform 1 (CO4A_HUMAN) complement C4-A P0C0L4K.MRPSTDTITVMVENSHGLR.V 0.65 isoform 1 (CO4A_HUMAN) complement C4-AP0C0L4 K.SCGLHQLLR.G 0.74 isoform 1 (CO4A_HUMAN) complement C4-A P0C0L4K.VGLSGMAIADVTLLSGFHALR.A 0.61 isoform 1 (CO4A_HUMAN) complement C4-AP0C0L4 K.YVLPNFEVK.I 0.64 isoform 1 (CO4A_HUMAN) complement C4-A P0C0L4R.ALEILQEEDLIDEDDIPVR.S 0.64 isoform 1 (CO4A_HUMAN) complement C4-AP0C0L4 R.ECVGFEAVQEVPVGLVQPASATLY 0.62 isoform 1 (CO4A_HUMAN) DYYNPER.Rcomplement C4-A P0C0L4 R.EELVYELNPLDHR.G 0.66 isoform 1 (CO4A_HUMAN)complement C4-A P0C0L4 R.STQDTVIALDALSAYWIASHTTE 0.70 isoform 1(CO4A_HUMAN) ER.G complement C4-A P0C0L4 R.VGDTLNLNLR.A 0.79 isoform 1(CO4A_HUMAN) complement C4-A P0C0L4 R.VHYTVCIWR.N 0.65 isoform 1(CO4A_HUMAN) complement C4-B-like P0C0L5 K.GLCVATPVQLR.V 1.00preproprotein (CO4B_HUMAN) complement C4-B-like P0C0L5 K.KYVLPNFEVK.I0.60 preproprotein (CO4B_HUMAN) complement C4-B-like P0C0L5K.VDFTLSSERDFALLSLQVPLKDAK.S 0.74 preproprotein (CO4B_HUMAN)complement C4-B-like P0C0L5 R.EMSGSPASGIPVK.V 0.72 preproprotein(CO4B_HUMAN) complement C4-B-like P0C0L5 R.GCGEQTM*IYLAPTLAASR.Y 0.75preproprotein (CO4B_HUMAN) complement C4-B-like P0C0L5R.NGESVKLHLETDSLALVALGALDTA 0.85 preproprotein (CO4B_HUMAN) LYAAGSK.Scomplement C5 P01031 R.IPLDLVPK.T 0.65 preproprotein (CO5_HUMAN)complement C5 P01031 R.SYFPESWLWEVHLVPR.R 0.63 preproprotein (CO5_HUMAN)complement C5 P01031 R.YGGGFYSTQDTINAIEGLTEYSLL 0.62 preproprotein(CO5_HUMAN) VK.Q complement P13671 K.ENPAVIDFELAPIVDLVR.N 0.63component C6 (CO6_HUMAN) precursor complement P07357K.YNPVVIDFEMQPIHEVLR.H 0.61 component C8 alpha (CO8A_HUMAN)chain precursor complement P07357 R.HTSLGPLEAK.R 0.65 component C8 alpha(CO8A_HUMAN) chain precursor complement P07358K.C*QHEMDQYWGIGSLASGINLFTN 0.61 component C8 beta (CO8B_HUMAN)SFEGPVLDHR.Y chain preproprotein complement P07358 K.SGFSFGFK.I 0.64component C8 beta (CO8B_HUMAN) chain preproprotein complement P07358R.DTMVEDLVVLVR.G 0.77 component C8 beta (CO8B_HUMAN) chain preproproteincomplement P07360 K.ANFDAQQFAGTWLLVAVGSACR.F 0.63 component C8 gamma(CO8G_HUMAN) chain precursor complement P07360 R.AEATTLHVAPQGTAMAVSTFR.K0.61 component C8 gamma (CO8G_HUMAN) chain precursor complement P02748R.DVVLTTTFVDDIK.A 0.73 component C9 (CO9_HUMAN) precursor complementP02748 R.RPWNVASLIYETK.G 0.66 component C9 (CO9_HUMAN) precursorcomplement factor B P00751 K.ISVIRPSK.G 0.70 preproprotein (CFAB_HUMAN)complement factor B P00751 K.VASYGVKPR.Y 0.63 preproprotein (CFAB_HUMAN)complement factor B P00751 R.DFHINLFQVLPWLK.E 0.68 preproprotein(CFAB_HUMAN) complement factor B P00751 R.DLLYIGK.D 0.63 preproprotein(CFAB_HUMAN) complement factor B P00751 R.GDSGGPLIVHK.R 0.63preproprotein (CFAB_HUMAN) complement factor B P00751 R.LEDSVTYHCSR.G0.68 preproprotein (CFAB_HUMAN) complement factor B P00751R.LPPTTTCQQQK.E 0.68 preproprotein (CFAB_HUMAN) complement factor HP08603 K.CLHPCVISR.E 0.62 isoform a precursor (CFAH_HUMAN)complement factor H P08603 K.CTSTGWIPAPR.C 0.74 isoform a precursor(CFAH_HUMAN) complement factor H P08603 K.IDVHLVPDR.K 0.66isoform a precursor (CFAH_HUMAN) complement factor H P08603K.IVSSAMEPDREYHFGQAVR.F 0.67 isoform a precursor (CFAH_HUMAN)complement factor H P08603 K.SIDVACHPGYALPK.A 0.67 isoform a precursor(CFAH_HUMAN) complement factor H P08603 K.VSVLCQENYLIQEGEEITCKDGR.W 0.63isoform a precursor (CFAH_HUMAN) complement factor H P08603K.WSSPPQCEGLPCK.S 0.60 isoform a precursor (CFAH_HUMAN)complement factor H P08603 R.EIMENYNIALR.W 0.61 isoform a precursor(CFAH_HUMAN) complement factor H P08603 R.RPYFPVAVGK.Y 0.83isoform a precursor (CFAH_HUMAN) complement factor H P08603R.WQSIPLCVEK.I 0.63 isoform a precursor (CFAH_HUMAN) complement factor IP05156 R.YQIWTTVVDWIHPDLKR.I 0.72 preproprotein (CFAI_HUMAN)corticosteroid-binding P08185 K.AVLQLNEEGVDTAGSTGVTLNLTSK 0.61globulin precursor (CBG_HUMAN) PIILR.F corticosteroid-binding P08185R.GLASANVDFAFSLYK.H 0.66 globulin precursor (CBG_HUMAN)fibrinogen alpha chain P02671 K.TFPGFFSPMLGEFVSETESR.G 0.62isoform alpha-E (FIBA_HUMAN) preproprotein gelsolin isoform b P06396K.FDLVPVPTNLYGDFFTGDAYVILK.T 0.66 (GELS_HUMAN) gelsolin isoform b P06396K.QTQVSVLPEGGETPLFK.Q 0.66 (GELS_HUMAN) gelsolin isoform b P06396K.TPSAAYLWVGTGASEAEK.T 0.71 (GELS_HUMAN) gelsolin isoform b P06396R.AQPVQVAEGSEPDGFWEALGGK.A 0.67 (GELS_HUMAN) gelsolin isoform b P06396R.IEGSNKVPVDPATYGQFYGGDSYIIL 0.60 (GELS_HUMAN) YNYR.H gelsolin isoform bP06396 R.VEKFDLVPVPTNLYGDFFTGDAYVI 0.73 (GELS_HUMAN) LK.Tgelsolin isoform b P06396 R.VPFDAATLHTSTAMAAQHGMDD 0.63 (GELS_HUMAN)DGTGQK.Q glutathione peroxidase P22352 K.FLVGPDGIPIMR.W 0.60 3 precursor(GPX3_HUMAN) hemopexin precursor P02790 K.ALPQPQNVTSLLGCTH.- 0.63(HEMO_HUMAN) hemopexin precursor P02790 K.SLGPNSCSANGPGLYLIHGPNLYCY 0.68(HEMO_HUMAN) SDVEK.L hemopexin precursor P02790 R.DGWHSWPIAHQWPQGPSAVDAA0.63 (HEMO_HUMAN) FSWEEK.L hemopexin precursor P02790R.GECQAEGVLFFQGDR.E 0.67 (HEMO_HUMAN) hemopexin precursor P02790R.GECQAEGVLFFQGDREWFWDLAT 0.67 (HEMO_HUMAN) GTM*K.E hemopexin precursorP02790 R.LEKEVGTPHGIILDSVDAAFICPGSS 0.75 (HEMO_HUMAN) R.Lhemopexin precursor P02790 R.LWWLDLK.S 0.62 (HEMO_HUMAN)hemopexin precursor P02790 R.WKNFPSPVDAAFR.Q 0.68 (HEMO_HUMAN)heparin cofactor 2 P05546 K.DQVNTFDNIFIAPVGISTAMGMISL 0.60 precursor(HEP2_HUMAN) GLK.G insulin-like growth P35858 K.ANVFVQLPR.L 0.71factor-binding protein (ALS_HUMAN) complex acid labile subunit isoform 2precursor insulin-like growth P35858 R.LEALPNSLLAPLGR.L 0.61factor-binding protein (ALS_HUMAN) complex acid labile subunit isoform 2precursor insulin-like growth P35858 R.LFQGLGK.L 0.68factor-binding protein (ALS_HUMAN) complex acid labile subunit isoform 2precursor insulin-like growth P35858 R.NLIAAVAPGAFLGLK.A 0.76factor-binding protein (ALS_HUMAN) complex acid labile subunit isoform 2precursor insulin-like growth P35858 R.TFTPQPPGLER.L 0.73factor-binding protein (ALS_HUMAN) complex acid labile subunit isoform 2precursor inter-alpha-trypsin P19827 K.Q*LVHHFEIDVDIFEPQGISK.L 0.69inhibitor heavy chain (ITIH1_HUMAN) H1 isoform a precursorinter-alpha-trypsin P19827 K.VTFQLTYEEVLK.R 0.61 inhibitor heavy chain(ITIH1_HUMAN) H1 isoform a precursor inter-alpha-trypsin P19827K.VTFQLTYEEVLKR.N 0.70 inhibitor heavy chain (ITIH1_HUMAN)H1 isoform a precursor inter-alpha-trypsin P19827R.GIEILNQVQESLPELSNHASILIMLT 0.62 inhibitor heavy chain (ITIH1_HUMAN)DGDPTEGVTDR.S H1 isoform a precursor inter-alpha-trypsin P19827R.GM*ADQDGLKPTIDKPSEDSPPLE 0.79 inhibitor heavy chain (ITIH1_HUMAN)M*LGPR.R H1 isoform a precursor inter-alpha-trypsin P19827R.KAAISGENAGLVR.A 0.78 inhibitor heavy chain (ITIH1_HUMAN)H1 isoform a precursor inter-alpha-trypsin P19823K.AGELEVFNGYFVHFFAPDNLDPI 0.64 inhibitor heavy chain (ITIH2_HUMAN) PK.NH2 precursor inter-alpha-trypsin P19823 K.FYNQVSTPLLR.N 0.68inhibitor heavy chain (ITIH2_HUMAN) H2 precursor inter-alpha-trypsinP19823 K.VQFELHYQEVK.W 0.68 inhibitor heavy chain (ITIH2_HUMAN)H2 precursor inter-alpha-trypsin P19823 R.ETAVDGELVVLYDVK.R 0.63inhibitor heavy chain (ITIH2_HUMAN) H2 precursor inter-alpha-trypsinP19823 R.IYLQPGR.L 0.75 inhibitor heavy chain (ITIH2_HUMAN) H2 precursorinter-alpha-trypsin Q06033 R.LWAYLTIEQLLEK.R 0.60 inhibitor heavy chain(ITIH3_HUMAN) H3 preproprotein inter-alpha-trypsin Q14624K.ITFELVYEELLK.R 0.60 inhibitor heavy chain (ITIH4_HUMAN)H4 isoform 1 precursor inter-alpha-trypsin Q14624 K.LQDRGPDVLTATVSGK.L0.67 inhibitor heavy chain (ITIH4_HUMAN) H4 isoform 1 precursorinter-alpha-trypsin Q14624 K.TGLLLLSDPDKVTIGLLFWDGRGEG 0.63inhibitor heavy chain (ITIH4_HUMAN) LR.L H4 isoform 1 precursorinter-alpha-trypsin Q14624 K.WKETLFSVM*PGLK.M 0.79 inhibitor heavy chain(ITIH4_HUMAN) H4 isoform 1 precursor inter-alpha-trypsin Q14624R.AISGGSIQIENGYFVHYFAPEGLTT 0.60 inhibitor heavy chain (ITIH4_HUMAN)M*PK.N H4 isoform 1 precursor inter-alpha-trypsin Q14624R.AISGGSIQIENGYFVHYFAPEGLTT 0.65 inhibitor heavy chain (ITIH4_HUMAN)MPK.N H4 isoform 1 precursor inter-alpha-trypsin Q14624R.ANTVQEATFQMELPK.K 0.68 inhibitor heavy chain (ITIH4_HUMAN)H4 isoform 1 precursor inter-alpha-trypsin Q14624R.SFAAGIQALGGTNINDAMLMAVQ 0.64 inhibitor heavy chain (ITIH4_HUMAN)LLDSSNQEER.L H4 isoform 1 precursor inter-alpha-trypsin Q14624R.VQGNDHSATR.E 0.63 inhibitor heavy chain (ITIH4_HUMAN)H4 isoform 1 precursor inter-alpha-trypsin Q14624 K.ITFELVYEELLKR.R 0.60inhibitor heavy chain (ITIH4_HUMAN) H4 isoform 2 precursorinter-alpha-trypsin Q14624 K.VTIGLLFWDGR.G 0.65 inhibitor heavy chain(ITIH4_HUMAN) H4 isoform 2 precursor inter-alpha-trypsin Q14624R.LWAYLTIQQLLEQTVSASDADQQA 0.68 inhibitor heavy chain (ITIH4_HUMAN) LR.NH4 isoform 2 precursor kallistatin precursor P29622K.LFHTNFYDTVGTIQLINDHVK.K 0.73 (KAIN_HUMAN) kininogen-1 isoform 2 P01042K.ENFLFLTPDCK.S 0.64 precursor (KNG1_HUMAN) kininogen-1 isoform 2 P01042K.IYPTVNCQPLGMISLMK.R 0.64 precursor (KNG1_HUMAN) kininogen-1 isoform 2P01042 K.KIYPTVNCQPLGMISLMK.R 0.78 precursor (KNG1_HUMAN)kininogen-1 isoform 2 P01042 K.SLWNGDTGECTDNAYIDIQLR.I 0.67 precursor(KNG1_HUMAN) lumican precursor P51884 K.ILGPLSYSK.I 0.60 (LUM_HUMAN)N-acetylmuramoyl-L- Q96PD5 K.EYGVVLAPDGSTVAVEPLLAGLEAG 0.61alanine amidase (PGRP2_HUMAN) LQGR.R precursor N-acetylmuramoyl-L-Q96PD5 R.EGKEYGVVLAPDGSTVAVEPLLAGL 0.69 alanine amidase (PGRP2_HUMAN)EAGLQGR.R precursor N-acetylmuramoyl-L- Q96PD5R.Q*NGAALTSASILAQQVWGTLVLL 0.60 alanine amidase (PGRP2_HUMAN) QR.Lprecursor pigment epithelium- P36955 K.IAQLPLTGSMSIIFFLPLK.V 0.65derived factor (PEDF_HUMAN) precursor pigment epithelium- P36955R.SSTSPTTNVLLSPLSVATALSALSLG 0.79 derived factor (PEDF_HUMAN) AEQR.Tprecursor plasma kallikrein P03952 K.VAEYMDWILEK.T 0.62 preproprotein(KLKB1_HUMAN) plasma kallikrein P03952 R.C*LLFSFLPASSINDMEKR.F 0.60preproprotein (KLKB1_HUMAN) plasma kallikrein P03952 R.C*QFFSYATQTFHK.A0.60 preproprotein (KLKB1_HUMAN) plasma kallikrein P03952R.CLLFSFLPASSINDMEK.R 0.76 preproprotein (KLKB1_HUMAN)plasma protease C1 P05155 R.LVLLNAIYLSAK.W 0.96 inhibitor precursor(IC1_HUMAN) pregnancy zone protein P20742 R.NALFCLESAWNVAK.E 0.67precursor (PZP_HUMAN) pregnancy zone protein P20742 R.NQGNTWLTAFVLK.T0.61 precursor (PZP_HUMAN) pregnancy-specific Q00887R.SNPVILNVLYGPDLPR.I 0.62 beta-1-glycoprotein 9 (PSG9_HUMAN) precursorprenylcysteine oxidase Q9UHG3 K.IAIIGAGIGGTSAAYYLR.Q 0.71 1 precursor(PCYOX_HUMAN) protein AMBP P02760 K.WYNLAIGSTCPWLK.K 0.77 preproprotein(AMBP_HUMAN) protein AMBP P02760 R.TVAACNLPIVR.G 0.66 preproprotein(AMBP_HUMAN) prothrombin P00734 R.IVEGSDAEIGMSPWQVMLFR.K 0.62preproprotein (THRB_HUMAN) prothrombin P00734 R.RQECSIPVCGQDQVTVAMTPR.S0.69 preproprotein (THRB_HUMAN) prothrombin P00734 R.TFGSGEADCGLRPLFEK.K0.61 preproprotein (THRB_HUMAN) retinol-binding protein P02753R.FSGTWYAMAK.K 0.60 4 precursor (RET4_HUMAN) retinol-binding proteinP02753 R.LLNNWDVCADMVGTFTDTEDPAK.F 0.64 4 precursor (RET4_HUMAN)serum amyloid P- P02743 R.GYVIIKPLVWV.- 0.62 component precursor(SAMP_HUMAN) sex hormone-binding P04278 K.VVLSSGSGPGLDLPLVLGLPLQLK.L0.60 globulin isoform 1 (SHBG_HUMAN) precursor sex hormone-bindingP04278 R.TWDPEGVIFYGDTNPKDDWFM*L 0.75 globulin isoform 1 (SHBG_HUMAN)GLR.D precursor sex hormone-binding P04278 R.TWDPEGVIFYGDTNPKDDWFMLG0.74 globulin isoform 1 (SHBG_HUMAN) LR.D precursor thrombospondin-1P07996 K.GFLLLASLR.Q 0.70 precursor (TSP1_HUMAN) thyroxine-bindingP05543 K.AVLHIGEK.G 0.85 globulin precursor (THBG_HUMAN)thyroxine-binding P05543 K.FSISATYDLGATLLK.M 0.65 globulin precursor(THBG_HUMAN) thyroxine-binding P05543 K.KELELQIGNALFIGK.H 0.61globulin precursor (THBG_HUMAN) thyroxine-binding P05543K.MSSINADFAFNLYR.R 0.67 globulin precursor (THBG_HUMAN)transforming growth Q15582 R.LTLLAPLNSVFK.D 0.65 factor-beta-induced(BGH3_HUMAN) protein ig-h3 precursor transthyretin precursor P02766R.GSPAINVAVHVFR.K 0.67 (TTHY_HUMAN) uncharacterized Q8ND61 K.MPSHLMLAR.K0.64 protein C3orf20 (CC020_HUMAN) isoform 1 vitamin D-binding P02774K.ELPEHTVK.L 0.75 protein isoform 1 (VTDB_HUMAN) precursorvitamin D-binding P02774 K.EYANQFMWEYSTNYGQAPLSLLVS 0.69protein isoform 1 (VTDB_HUMAN) YTK.S precursor vitamin D-binding P02774K.HLSLLTTLSNR.V 0.65 protein isoform 1 (VTDB_HUMAN) precursorvitamin D-binding P02774 K.HQPQEFPTYVEPTNDEICEAFR.K 0.64protein isoform 1 (VTDB_HUMAN) precursor vitamin D-binding P02774K.LAQKVPTADLEDVLPLAEDITNIL 0.73 protein isoform 1 (VTDB_HUMAN) SK.Cprecursor vitamin D-binding P02774 K.LCDNLSTK.N 0.70 protein isoform 1(VTDB_HUMAN) precursor vitamin D-binding P02774 K.LCMAALK.H 0.63protein isoform 1 (VTDB_HUMAN) precursor vitamin D-binding P02774K.SCESNSPFPVHPGTAECCTK.E 0.63 protein isoform 1 (VTDB_HUMAN) precursorvitamin D-binding P02774 K.SYLSMVGSCCTSASPTVCFLK.E 0.61protein isoform 1 (VTDB_HUMAN) precursor vitamin D-binding P02774K.TAMDVFVCTYFM*PAAQLPELPDV 0.61 protein isoform 1 (VTDB_HUMAN) ELPTNK.Dprecursor vitamin D-binding P02774 K.VLEPTLK.S 0.69 protein isoform 1(VTDB_HUMAN) precursor vitamin D-binding P02774 R.KFPSGTFEQVSQLVK.E 0.66protein isoform 1 (VTDB_HUMAN) precursor vitamin D-binding P02774R.THLPEVFLSK.V 0.62 protein isoform 1 (VTDB_HUMAN) precursorvitamin D-binding P02774 R.TSALSAK.S 0.74 protein isoform 1 (VTDB_HUMAN)precursor vitronectin precursor P04004 R.GQYCYELDEK.A 0.73 (VTNC_HUMAN)vitronectin precursor P04004 R.M*DWLVPATCEPIQSVFFFSGDK.Y 0.64(VTNC_HUMAN) vitronectin precursor P04004 R.Q*PQFISR.D 0.63 (VTNC_HUMAN)

TABLE 10 Significant peptides (AUC > 0.6) for both X!Tandem and SequestUniprot ID Protein description (name) Peptide XT_AUC S_AUCafamin precursor P43652 K.HFQNLGK.D 0.74 0.61 (AFAM_HUMAN)afamin precursor P43652 R.RHPDLSIPELL 0.67 0.63 (AFAM_HUMAN) R.Iafamin precursor P43652 R.TINPAVDHCC 0.66 0.86 (AFAM_HUMAN) K.Talpha-1-antichymotrypsin P01011 KITDLIKDLDSQ 0.71 0.73 precursor(AACT_HUMAN) TMMVLVNYIFF K.A alpha-1-antichymotrypsin P01011R.DYNLNDILLQ 0.74 0.62 precursor (AACT_HUMAN) LGIEEAFTSK.Aalpha-1-antichymotrypsin P01011 R.GTHVDLGLAS 0.76 0.61 precursor(AACT_HUMAN) ANVDFAFSLYK.Q alpha-1B-glycoprotein P04217 K.SLPAPWLSMA0.71 0.65 precursor (A1BG_HUMAN) PVSWITPGLK.T alpha-2-antiplasmin P08697K.GFPIKEDFLEQ 0.66 0.69 isoform a precursor (A2AP_HUMAN) SEQLFGAKPVSLTGK.Q alpha-2-antiplasmin P08697 K.HQMDLVATL 0.67 0.60isoform a precursor (A2AP_HUMAN) SQLGLQELFQAP DLR.G alpha-2-antiplasminP08697 R.QLTSGPNQEQ 0.66 0.61 isoform a precursor (A2AP_HUMAN)VSPLTLLK.L alpha-2-HS-glycoprotein P02765 R.AQLVPLPPST 0.64 0.63preproprotein (FETUA_HUMAN) YVEFTVSGTDC VAK.E angiotensinogen P01019K.DPTFIPAPIQA 0.69 0.69 preproprotein (ANGT_HUMAN) K.T angiotensinogenP01019 R.FM*QAVTGW 0.65 0.65 preproprotein (ANGT_HUMAN) K.Tantithrombin-III P01008 K.ANRPFLVFI 0.72 0.60 precursor (ANT3_HUMAN) R.Eantithrombin-III P01008 K.GDDITMVLIL 0.69 0.68 precursor (ANT3_HUMAN)PKPEK.S antithrombin-III P01008 R.DIPMNPMCIY 0.63 0.78 precursor(ANT3_HUMAN) R.S apolipoprotein A-IV P06727 K.KLVPFATELH 0.65 0.77precursor (APOA4_HUMAN) ER.L apolipoprotein A-IV P06727 K.SLAELGGHLD0.60 0.75 precursor (APOA4_HUMAN) QQVEEFR.R apolipoprotein B-100 P04114K.ALYWVNGQV 0.61 0.63 precursor (APOB_HUMAN) PDGVSK.Vapolipoprotein B-100 P04114 K.FIIPGLK.L 0.64 0.68 precursor (APOB_HUMAN)apolipoprotein B-100 P04114 K.FSVPAGIVIPS 0.63 0.63 precursor(APOB_HUMAN) FQALTAR.F apolipoprotein B-100 P04114 K.IEGNLIFDPNN 0.630.65 precursor (APOB_HUMAN) YLPK.E apolipoprotein B-100 P04114K.LNDLNSVLV 0.91 0.88 precursor (APOB_HUMAN) MPTFHVPFTDL QVPSCK.Lapolipoprotein B-100 P04114 K.VELEVPQLCS 0.60 0.61 precursor(APOB_HUMAN) FILK.T apolipoprotein B-100 P04114 K.VNWEEEAAS 0.60 0.73precursor (APOB_HUMAN) GLLTSLK.D apolipoprotein B-100 P04114R.ATLYALSHAV 0.78 0.80 precursor (APOB_HUMAN) NNYHK.Tapolipoprotein B-100 P04114 R.TGISPLALIK.G 0.64 0.77 precursor(APOB_HUMAN) apolipoprotein B-100 P04114 R.TLQGIPQMIG 0.65 0.66precursor (APOB_HUMAN) EVIR.K apolipoprotein C-III P02656 K.DALSSVQESQ0.80 0.69 precursor (APOC3_HUMAN) VAQQAR.G apolipoprotein C-IV P55056R.DGWQWFWSP 0.63 0.67 precursor (APOC4_HUMAN) STFR.G apolipoprotein EP02649 K.VQAAVGTSA 0.70 0.72 precursor (APOE_HUMAN) APVPSDNH.-apolipoprotein E P02649 R.WELALGR.F 0.88 0.60 precursor (APOE_HUMAN)beta-2-microglobulin P61769 K.SNFLNCYVSG 0.60 0.70 precursor(B2MG_HUMAN) FHPSDIEVDLLK.N bone marrow P13727 R.GGHCVALCT 0.83 0.86proteoglycan isoform 1 (PRG2_HUMAN) R.G preproproteincarboxypeptidase B2 Q96IY4 R.LVDFYVMPV 0.61 0.65 preproprotein(CBPB2_HUMAN) VNVDGYDYSW K.K carboxypeptidase B2 Q96IY4 R.YTHGHGSETL0.60 0.68 preproprotein (CBPB2_HUMAN) YLAPGGGDDWI YDLGIK.Ycarboxypeptidase N P22792 K.LSNNALSGLP 0.65 0.67 subunit 2 precursor(CPN2_HUMAN) QGVFGK.L carboxypeptidase N P22792 K.TLNLAQNLLA 0.67 0.69subunit 2 precursor (CPN2_HUMAN) QLPEELFHPLTS LQTLK.L carboxypeptidase NP22792 R.WLNVQLSP 0.74 0.67 subunit 2 precursor (CPN2_HUMAN) R.Qceruloplasmin precursor P00450 K.GDSVVWYLF 0.90 0.72 (CERU_HUMAN)SAGNEADVHGI YFSGNTYLWR.G ceruloplasmin precursor P00450 K.MYYSAVDPT 0.700.82 (CERU_HUMAN) K.D ceruloplasmin precursor P00450 R.GPEEEHLGIL 0.600.65 (CERU_HUMAN) GPVIWAEVGDTI R.V ceruloplasmin precursor P00450R.IDTINLFPATL 0.66 0.70 (CERU_HUMAN) FDAYMVAQNP GEWMLSCQNL NHLK.Aceruloplasmin precursor P00450 R.SGAGTEDSAC 0.88 0.92 (CERU_HUMAN)IPWAYYSTVDQ VKDLYSGLIGPL IVCR.R cholinesterase precursor P06276K.IFFPGVSEFG 0.70 0.63 (CHLE_HUMAN) K.E cholinesterase precursor P06276R.AILQSGSFNAP 0.75 0.77 (CHLE_HUMAN) WAVTSLYEAR.Nchorionic gonadotropin, P01233 R.VLQGVLPALP 0.60 0.75 beta polypeptide 8(CGHB_HUMAN) QVVCNYR.D precursor chorionic P01243 R.ISLLLIESWLE 0.830.63 somatomammotropin (CSH_HUMAN) PVR.F hormone 2 isoform 2 precursorcoagulation factor XII P00748 R.LHEAFSPVSY 0.60 0.66 precursor(FA12_HUMAN) QHDLALLR.L coagulation factor XII P00748 R.TTLSGAPCQP 0.690.82 precursor (FA12_HUMAN) WASEATYR.N complement C1q P02745 K.GLFQVVSGG0.65 0.60 subcomponent subunit A (C1QA_HUMAN) MVLQLQQGDQ precursorVWVEKDPK.K complement C1r P00736 K.VLNYVDWIK 0.80 0.76subcomponent precursor (C1R_HUMAN) K.E complement C1s P09871K.SNALDIIFQTD 0.62 0.77 subcomponent precursor (C1S_HUMAN) LTGQK.Kcomplement C4-A P0C0L4 K.EGAIHREELV 0.76 0.75 isoform 1 (CO4A_HUMAN)YELNPLDHR.G complement C4-A P0C0L4 K.ITQVLHFTK.D 0.63 0.62 isoform 1(CO4A_HUMAN) complement C4-A P0C0L4 K.SHALQLNNR.Q 0.66 0.71 isoform 1(CO4A_HUMAN) complement C4-A P0C0L4 R.AVGSGATFSH 0.65 0.60 isoform 1(CO4A_HUMAN) YYYM*ILSR.G complement C4-A P0C0L4 R.EPFLSCCQFA 0.64 0.72isoform 1 (CO4A_HUMAN) ESLR.K complement C4-A P0C0L4 R.GHLFLQTDQP 0.630.76 isoform 1 (CO4A_HUMAN) IYNPGQR.V complement C4-A P0C0L4R.GLEEELQFSL 0.68 0.68 isoform 1 (CO4A_HUMAN) GSK.I complement C4-AP0C0L4 R.GSFEFPVGDA 0.67 0.70 isoform 1 (CO4A_HUMAN) VSK.Vcomplement C4-A P0C0L4 R.LLATLCSAEV 0.61 0.71 isoform 1 (CO4A_HUMAN)CQCAEGK.C complement C4-A P0C0L4 R.VQQPDCREPF 0.65 0.83 isoform 1(CO4A_HUMAN) LSCCQFAESLRK.K complement C4-A P0C0L4 R.YIYGKPVQGV 0.820.76 isoform 1 (CO4A_HUMAN) AYVR.F complement C5 P01031 K.ITHYNYLILS0.66 0.69 preproprotein (CO5_HUMAN) K.G complement C5 P01031R.ENSLYLTAFT 0.60 0.68 preproprotein (CO5_HUMAN) VIGIR.K complement C5P01031 R.KAFDICPLVK.I 0.77 0.65 preproprotein (CO5_HUMAN) complement C5P01031 R.VDDGVASFVL 0.68 0.61 preproprotein (CO5_HUMAN) NLPSGVTVLEFNVK.T complement component P13671 K.TFSEWLESVK 0.94 0.64 C6 precursor(CO6_HUMAN) ENPAVIDFELAP IVDLVR.N complement component P13671R.IFDDFGTHYF 0.78 0.75 C6 precursor (CO6_HUMAN) TSGSLGGVYDL LYQFSSEELK.Ncomplement component P10643 K.ELSHLPSLYD 0.69 0.71 C7 precursor(CO7_HUMAN) YSAYR.R complement component P10643 R.RYSAWAESV 0.71 0.70C7 precursor (CO7_HUMAN) TNLPQVIK.Q complement component P07357K.YNPVVIDFEM* 0.68 0.73 C8 alpha chain precursor (CO8A_HUMAN) QPIHEVLR.Hcomplement component P07358 K.VEPLYELVTA 0.69 0.70 C8 beta chain(CO8B_HUMAN) TDFAYSSTVR.Q preproprotein complement component P07358R.SLM*LHYEFL 0.61 0.65 C8 beta chain (CO8B_HUMAN) QR.V preproproteincomplement component P07360 K.YGFCEAADQF 0.78 0.76 C8 gamma chain(CO8G_HUMAN) HVLDEVRR.- precursor complement component P07360R.FLQEQGHR.A 0.63 0.69 C8 gamma chain (CO8G_HUMAN) precursorcomplement component P07360 R.KLDGICWQV 0.75 0.70 C8 gamma chain(CO8G_HUMAN) R.Q precursor complement component P07360 R.SLPVSDSVLS 0.700.60 C8 gamma chain (CO8G_HUMAN) GFEQR.V precursor complement componentP02748 R.GTVIDVTDFV 0.68 0.69 C9 precursor (CO9_HUMAN) NWASSINDAPVLISQK.L complement factor B P00751 K.NPREDYLDV 0.72 0.77 preproprotein(CFAB_HUMAN) YVFGVGPLVNQ VNINALASK.K complement factor B P00751R.GDSGGPLIVH 0.60 0.76 preproprotein (CFAB_HUMAN) KR.Scomplement factor B P00751 R.HVIILMTDGL 0.60 0.64 preproprotein(CFAB_HUMAN) HNM*GGDPITVI DEIR.D complement factor B P00751 R.KNPREDYLDV0.63 0.63 preproprotein (CFAB_HUMAN) YVFGVGPLVNQ VNINALASK.Kcomplement factor H P08603 K.SCDIPVFMNA 0.62 0.71 isoform a precursor(CFAH_HUMAN) R.T complement factor H P08603 K.SPPEISHGVV 0.88 0.88isoform a precursor (CFAH_HUMAN) AHMSDSYQYGE EVTYK.C complement factor HP08603 K.TDCLSLPSFE 0.61 0.66 isoform a precursor (CFAH_HUMAN)NAIPMGEKK.D complement factor I P05156 K.RAQLGDLPW 0.71 0.74preproprotein (CFAI_HUMAN) QVAIK.D complement factor I P05156K.SLECLHPGT 0.64 0.81 preproprotein (CFAI_HUMAN) K.F complement factor IP05156 R.TMGYQDFAD 0.73 0.75 preproprotein (CFAI_HUMAN) VVCYTQK.Aextracellular matrix Q16610 R.ELLALIQLE 0.69 0.65 protein 1 isoform 3(ECM1_HUMAN) R.E precursor gelsolin isoform a P06396 R.VPEARPNSMV 0.760.62 precursor (GELS_HUMAN) VEHPEFLK.A glutathione peroxidase 3 P22352R.LFWEPMK.V 0.69 0.67 precursor (GPX3_HUMAN) hemopexin precursor P02790R.DVRDYFMPCP 0.70 0.72 (HEMO_HUMAN) GR.G heparin cofactor 2 P05546K.DALENIDPAT 0.61 0.65 precursor (HEP2_HUMAN) QMMILNCIYFK.Gheparin cofactor 2 P05546 K.GLIKDALENI 0.64 0.64 precursor (HEP2_HUMAN)DPATQMMILNC IYFK.G heparin cofactor 2 P05546 K.QFPILLDFK.T 0.61 0.69precursor (HEP2_HUMAN) heparin cofactor 2 P05546 R.VLKDQVNTF 0.88 0.75precursor (HEP2_HUMAN) DNIFIAPVGISTA MGMISLGLK.G insulin-like growthP35858 R.AFWLDVSHN 0.61 0.82 factor-binding protein (ALS_HUMAN) R.Lcomplex acid labile subunit isoform 2 precursor inter-alpha-trypsinP19827 K.ADVQAHGEG 0.61 0.74 inhibitor heavy chain H1 (ITIH1_HUMAN)QEFSITCLVDEE isoform a precursor EMKK.L inter-alpha-trypsin P19827K.ILGDM*QPGD 0.71 0.63 inhibitor heavy chain H1 (ITIH1_HUMAN)YFDLVLFGTR.V isoform a precursor inter-alpha-trypsin P19827 K.ILGDMQPGDY0.68 0.60 inhibitor heavy chain H1 (ITIH1_HUMAN) FDLVLFGTR.Visoform a precursor inter-alpha-trypsin P19827 K.NVVFVIDISGS 0.76 0.83inhibitor heavy chain H1 (ITIH1_HUMAN) MR.G isoform a precursorinter-alpha-trypsin P19827 K.TAFISDFAVT 0.74 0.63inhibitor heavy chain H1 (ITIH1_HUMAN) ADGNAFIGDIKD isoform a precursorK.V inter-alpha-trypsin P19827 R.GHMLENHVE 0.78 0.80inhibitor heavy chain H1 (ITIH1_HUMAN) R.L isoform a precursorinter-alpha-trypsin P19827 R.GM*ADQDGL 0.61 0.62inhibitor heavy chain H1 (ITIH1_HUMAN) KPTIDKPSEDSP isoform a precursorPLEMLGPR.R inter-alpha-trypsin P19827 R.LWAYLTIQEL 0.68 0.62inhibitor heavy chain H1 (ITIH1_HUMAN) LAK.R isoform a precursorinter-alpha-trypsin P19827 R.NHM*QYEIVI 0.67 0.65inhibitor heavy chain H1 (ITIH1_HUMAN) K.V isoform a precursorinter-alpha-trypsin P19823 K.AHVSFKPTVA 0.75 0.61inhibitor heavy chain H2 (ITIH2_HUMAN) QQR.I precursorinter-alpha-trypsin P19823 K.ENIQDNISLFS 0.80 0.93inhibitor heavy chain H2 (ITIH2_HUMAN) LGM*GFDVDYD precursor FLKR.Linter-alpha-trypsin P19823 K.ENIQDNISLFS 0.63 0.80inhibitor heavy chain H2 (ITIH2_HUMAN) LGMGFDVDYDF precursor LKR.Linter-alpha-trypsin P19823 K.HLEVDVWVIE 0.61 0.61inhibitor heavy chain H2 (ITIH2_HUMAN) PQGLR.F precursorinter-alpha-trypsin P19823 K.LWAYLTINQL 0.69 0.62inhibitor heavy chain H2 (ITIH2_HUMAN) LAER.S precursorinter-alpha-trypsin P19823 R.AEDHFSVIDF 0.65 0.63inhibitor heavy chain H2 (ITIH2_HUMAN) NQNIR.T precursorinter-alpha-trypsin P19823 R.FLHVPDTFEG 0.66 0.62inhibitor heavy chain H2 (ITIH2_HUMAN) HFDGVPVISK.G precursorinter-alpha-trypsin Q14624 K.ILDDLSPR.D 0.67 0.65inhibitor heavy chain H4 (ITIH4_HUMAN) isoform 1 precursorinter-alpha-trypsin Q14624 K.IPKPEASFSP 0.69 0.77inhibitor heavy chain H4 (ITIH4_HUMAN) R.R isoform 1 precursorinter-alpha-trypsin Q14624 K.SPEQQETVLD 0.63 0.69inhibitor heavy chain H4 (ITIH4_HUMAN) GNLIIR.Y isoform 1 precursorinter-alpha-trypsin Q14624 K.YIFHNFMER.L 0.66 0.61inhibitor heavy chain H4 (ITIH4_HUMAN) isoform 1 precursorinter-alpha-trypsin Q14624 R.FSSHVGGTLG 0.69 0.71inhibitor heavy chain H4 (ITIH4_HUMAN) QFYQEVLWGSP isoform 1 precursorAASDDGRR.T inter-alpha-trypsin Q14624 R.GPDVLTATVS 0.63 0.82inhibitor heavy chain H4 (ITIH4_HUMAN) GK.L isoform 1 precursorinter-alpha-trypsin Q14624 R.NMEQFQVSVS 0.78 0.60inhibitor heavy chain H4 (ITIH4_HUMAN) VAPNAK.I isoform 1 precursorinter-alpha-trypsin Q14624 R.RLDYQEGPPG 0.68 0.62inhibitor heavy chain H4 (ITIH4_HUMAN) VEISCWSVEL.- isoform 1 precursorkallistatin precursor P29622 K.IVDLVSELKK.D 0.75 0.67 (KAIN_HUMAN)kallistatin precursor P29622 R.VGSALFLSHN 0.70 0.74 (KAIN_HUMAN) LK.Fkininogen-1 isoform 2 P01042 K.IYPTVNCQPL 0.89 0.62 precursor(KNG1_HUMAN) GM*ISLM*K.R kininogen-1 isoform 2 P01042 K.TVGSDTFYSF 0.610.68 precursor (KNG1_HUMAN) K.Y kininogen-1 isoform 2 P01042R.DIPTNSPELEE 0.61 0.76 precursor (KNG1_HUMAN) TLTHTITK.Lkininogen-1 isoform 2 P01042 R.VQVVAGK.K 0.67 0.71 precursor(KNG1_HUMAN) lumican precursor P51884 R.FNALQYLR.L 0.68 0.76 (LUM_HUMAN)macrophage colony- P09603 K.VIPGPPALTLV 0.68 0.60 stimulating factor 1(CSF1_HUMAN) PAELVR.I receptor precursor monocyte differentiation P08571K.ITGTMPPLPLE 0.80 0.67 antigen CD14 precursor (CD14_HUMAN) ATGLALSSLR.LN-acetylmuramoyl-L- Q96PD5 K.EFTEAFLGCP 0.62 0.64 alanine amidase(PGRP2_HUMAN) AIHPR.C precursor N-acetylmuramoyl-L- Q96PD5 R.RVINLPLDSM0.63 0.62 alanine amidase (PGRP2_HUMAN) AAPWETGDTFP precursorDVVAIAPDVR.A phosphatidylinositol- P80108 R.GVFFSVNSWT 0.67 0.78glycan-specific (PHLD_HUMAN) PDSMSFIYK.A phospholipase D precursorpigment epithelium- P36955 K.EIPDEISILLLGVAHF 0.63 0.61derived factor precursor (PEDF_HUMAN) K.G pigment epithelium- P36955K.IAQLPLTGSM*SIIF 0.79 0.61 derived factor precursor (PEDF_HUMAN)FLPLK.V pigment epithelium- P36955 K.TVQAVLTVPK.L 0.75 0.79derived factor precursor (PEDF_HUMAN) pigment epithelium- P36955R.ALYYDLISSPDIHGT 0.60 0.73 derived factor precursor (PEDF_HUMAN)YKELLDTVTAPQK.N pigment epithelium- P36955 R.DTDTGALLFIGK.I 0.85 0.62derived factor precursor (PEDF_HUMAN) plasminogen isoform 1 P00747R.ELRPWCFTTDPNK 0.70 0.68 precursor (PLMN_HUMAN) R.Wplasminogen isoform 1 P00747 R.TECFITGWGETQGT 0.63 0.68 precursor(PLMN_HUMAN) FGAGLLK.E platelet basic protein P02775 K.GTHCNQVEVIATL0.60 0.61 preproprotein (CXCL7_HUMAN) K.D pregnancy zone protein P20742K.AVGYLITGYQR.Q 0.87 0.73 precursor (PZP_HUMAN) pregnancy zone proteinP20742 R.AVDQSVLLM*KPE 0.64 0.62 precursor (PZP_HUMAN) AELSVSSVYNLLTVK.Dpregnancy zone protein P20742 R.IQHPFTVEEFVLP 0.66 0.74 precursor(PZP_HUMAN) K.F pregnancy zone protein P20742 R.NELIPLIYLENPR.R 0.610.61 precursor (PZP_HUMAN) protein AMBP P02760 R.AFIQLWAFDAVK.G 0.720.67 preproprotein (AMBP_HUMAN) proteoglycan 4 isoform B Q92954K.GFGGLTGQIVAALS 0.70 0.72 precursor (PRG4_HUMAN) TAK.Yprothrombin preproprotein P00734 K.YGFYTHVFR.L 0.70 0.63 (THRB_HUMAN)prothrombin preproprotein P00734 R.IVEGSDAEIGM*SP 0.63 0.71 (THRB_HUMAN)WQVMLFR.K retinol-binding protein 4 P02753 K.KDPEGLFLQDNIVA 0.67 0.67precursor (RET4_HUMAN) EFSVDETGQMSATAK.G thyroxine-binding globulinP05543 K.AQWANPFDPSKTE 0.67 0.80 precursor (THBG_HUMAN) DSSSFLIDK.Tthyroxine-binding globulin P05543 K.GWVDLFVPK.F 0.67 0.64 precursor(THBG_HUMAN) thyroxine-binding globulin P05543 R.SFM*LLILER.S 0.65 0.68precursor (THBG_HUMAN) thyroxine-binding globulin P05543 R.SFMLLILER.S0.64 0.62 precursor (THBG_HUMAN) vitamin D-binding protein P02774K.EFSHLGKEDFTSLSL 0.74 0.61 isoform 1 precursor (VTDB_HUMAN) VLYSR.Kvitamin D-binding protein P02774 K.EYANQFM*WEYST 0.73 0.61isoform 1 precursor (VTDB_HUMAN) NYGQAPLSLLVSYTK.Svitamin D-binding protein P02774 K.HQPQEFPTYVEPTN 0.67 0.69isoform 1 precursor (VTDB_HUMAN) DEICEAFRK.D vitamin D-binding proteinP02774 K.SYLSM*VGSCCTSA 0.63 0.62 isoform 1 precursor (VTDB_HUMAN)SPTVCFLK.E vitamin D-binding protein P02774 K.TAM*DVFVCTYFM 0.63 0.60isoform 1 precursor (VTDB_HUMAN) PAAQLPELPDVELPT NK.Dvitamin D-binding protein P02774 K.VPTADLEDVLPLAE 0.70 0.71isoform 1 precursor (VTDB_HUMAN) DITNILSK.C vitronectin precursor P04004K.AVRPGYPK.L 0.68 0.77 (VTNC_HUMAN) vitronectin precursor P04004R.MDWLVPATCEPIQ 0.67 0.65 (VTNC_HUMAN) SVFFFSGDK.Yzinc-alpha-2-glycoprotein P25311 K.EIPAWVPFDPAAQI 0.63 0.67 precursor(ZA2G_HUMAN) TK.Q

The differentially expressed proteins identified by thehypothesis-independent strategy above, not already present in our MRM-MSassay, were candidates for incorporation into the MRM-MS assay. Twoadditional proteins (AFP, PGH1) of functional interest were alsoselected for MRM development. Candidates were prioritized by AUC andbiological function, with preference give for new pathways. Sequencesfor each protein of interest, were imported into Skyline software whichgenerated a list of tryptic peptides, m/z values for the parent ions andfragment ions, and an instrument-specific collision energy (McLean etal. Bioinformatics (2010) 26 (7): 966-968; McLean et al. Anal. Chem(2010) 82 (24): 10116-10124).

The list was refined by eliminating peptides containing cysteines andmethionines, and by using the shotgun data to select the charge state(s)and a subset of potential fragment ions for each peptide that hadalready been observed on a mass spectrometer.

After prioritizing parent and fragment ions, a list of transitions wasexported with a single predicted collision energy. Approximately 100transitions were added to a single MRM run. For development, MRM datawas collected on either a QTRAP 5500 (AB Sciex) or a 6490 QQQ (Agilent).Commercially available human female serum (from pregnant andnon-pregnant donors), was depleted and processed to tryptic peptides, asdescribed above, and used to “scan” for peptides of interest. In somecases, purified synthetic peptides were used for further optimization.For development, digested serum or purified synthetic peptides wereseparated with a 15 min acetonitrile gradient at 100 ul/min on a 2.1×50mM Poroshell 120 EC-C18 column (Agilent) at 40° C.

The MS/MS data was imported back into Skyline, where all chromatogramsfor each peptide were overlayed and used to identify a consensus peakcorresponding to the peptide of interest and the transitions with thehighest intensities and the least noise. Table 11, contains a list ofthe most intensely observed candidate transitions and peptides fortransfer to the MRM assay.

TABLE 11Candidate peptides and transitions for transferring to the MRM assayfragment ion, m/z, Protein Peptide m/z, charge charge, rank areaalpha-1-antichymotrypsin K.ADLSGITGAR.N  480.7591++ S[y7]-661.3628+[1]1437602 G[y6]-574.3307+[2]  637584 T[y4]-404.2252+[3]  350392L[y8]-774.4468+[4]  191870 G[y3]-303.1775+[5]  150575 I[y5]-517.3093+[6]  97828 alpha-1-antichymotrypsin K.EQLSLLDR.F  487.2693++S[y5]-603.3461[1]  345602 L[y6]-716.4301[2]  230046 L[y4]-516.3140[3] 143874 D[y2]-290.1459[4]  113381 D[y2]-290.1459[5]  113381Q[b2]-258.1084[6]   78157 alpha-1-antichymotrypsin K.ITLLSALVETR.T 608.3690++ S[y7]-775.4308+[1] 1059034 L[y8]-888.5149+[2]  541969T[b2]-215.1390+[3]  408819 L[y9]-1001.5990+[4]  438441V[y4]-504.2776+[5]  311293 L[y5]-617.3617+[6]  262544 L[b3]-328.2231+[7] 197526 T[y2]-276.1666+[8]  212816 E[y3]-405.2092+[9]  207163alpha-1-antichymotrypsin R.EIGELYLPK.F  531.2975++ G[y7]-819.4611+[2] 977307 L[y5]-633.3970+[3]  820582 Y[y4]-520.3130+[4]  400762L[y3]-357.2496+[5]  498958 P[y2]-244.1656+[1] 1320591 I[b2]-243.1339+[6] 303268 G[b3]-300.1554+[7]  305120 alpha-1-antichymotrypsinR.GTHVDLGLASA  742.3794+++ D[y8]-990.4931+[1]  154927 NVDFAFSLYK.QL[b8]-793.4203+[2]   51068 D[b5]-510.2307+[3]   45310 F[y7]-875.4662+[4]  42630 A[b9]-864.4574+[5]   43355 S[y4]-510.2922+[6]   45310F[y5]-657.3606+[7]   37330 V[y9]-1089.5615+[8]   32491G[b7]-680.3362+[9]   38185 Y[y2]-310.1761+[10]   36336N[b12]-1136.5695+[11]   16389 S[b10]-951.4894+[12]   16365L[b6]-623.3148+[13]   13687 L[y3]-423.2602+[14]   17156V[b4]-395.2037+[15]   10964 alpha-1-antichymotrypsin R.NLAVSQVVHK.A 547.8195++ A[y8]-867.5047+[1]  266203  365.5487+++ L[b2]-228.1343+[2] 314232 V[y7]-796.4676+[3]  165231 A[b3]-299.1714+[4]  173694S[y6]-697.3991+[5]  158512 H[y2]-284.1717+[6]  136431 V[b4]-398.2398+[7]  36099 S[b5]-485.2718+[8]   23836 S[y6]-697.3991+[1]  223443V[y3]-383.2401+[2]  112952 V[y4]-482.3085+[3]   84872 Q[y5]-610.3671+[4]  30835 inter-alpha-trypsin K.AAISGENAGLVR.A  579.3173++S[y9]-902.4690+[1]  518001 inhibitor heavy chain H1 G[y8]-815.4370+[2] 326256 N[y6]-629.3729+[3]  296670 S[b4]-343.1976+[4]  258172inter-alpha-trypsin K.GSLVQASEANL  668.6763+++ A[y7]-806.4155+[1] 304374 inhibitor heavy chain H1 QAAQDFVR.G A[y6]-735.3784+[2]  193844V[b4]-357.2132+[3]  294094 F[y3]-421.2558+[4]  167816 A[b6]-556.3089+[5] 149216 L[b11]-535.7775++[6]  156882 A[b13]-635.3253++[7]  249287A[y14]-760.3786++[8]  123723 F[b17]-865.9208++[9]   23057inter-alpha-trypsin K.TAFISDFAVTAD 1087.0442++ G[y4]-432.2453+[1]  22362 inhibitor heavy chain H1 GNAFIGDIK.D I[y5]-545.3293+[2]    8319A[b8]-853.4090+[3]    7006 G[y9]-934.4993+[4]    6755 F[y6]-692.3978+[5]   6193 V[b9]-952.4775+[6]    9508 inter-alpha-trypsin K.VTYDVSR.D 420.2165++ Y[y5]-639.3097+[1]  609348 inhibitor heavy chain H1T[b2]-201.1234+[2]  792556 D[y4]-476.2463+[3]  169546 V[y3]-361.2194+[4] 256946 Y[y5]-320.1585++[5]  110608 S[y2]-262.1510+[6]   50268Y[b3]-182.5970++[7]   10947 D[b4]-479.2136+[8]   13662inter-alpha-trypsin R.EVAFDLEIPK.T  580.8135++ P[y2]-244.1656+[1]2032509 inhibitor heavy chain H1 D[y6]-714.4032+[2]  672749A[y8]-932.5088+[3]  390837 L[y5]-599.3763+[4]  255527 F[y7]-861.4716+[5] 305087 inter-alpha-trypsin R.LWAYLTIQELLAK.R  781.4531++W[b2]-300.1707+[1]  602601 inhibitor heavy chain H1 A[b3]-371.2078+[2] 356967 T[y8]-915.5510+[3]  150419 Y[b4]-534.2711+[4]  103449I[y7]-814.5033+[5]   72044 Q[y6]-701.4192+[6]   66989 L[b5]-647.3552+[7]  99820 E[y5]-573.3606+[8]   44843 inter-alpha-trypsin K.FYNQVSTPLLR.N 669.3642++ S[y6]-686.4196+[1]  367330 inhibitor heavy chain H2V[y7]-785.4880+[2]  182396 P[y4]-498.3398+[3]  103638 Y[b2]-311.1390+[4]  52172 Q[b4]-553.2405+[5]   54270 N[b3]-425.1819+[6]   34567inter-alpha-trypsin K.HLEVDVWVIEPQGLR.F  597.3247+++ I[y7]-812.4625+[1] 206996 inhibitor heavy chain H2 P[y5]-570.3358+[2]  303693E[y6]-699.3784+[3]  126752 P[y5]-285.6715++[4]   79841inter-alpha-trypsin K.TAGLVR.S  308.6925++ A[b2]-173.0921+[1]  460019inhibitor heavy chain H2 G[y4]-444.2929+[2]  789068 V[y2]-274.1874+[3]  34333 G[b3]-230.1135+[4]   15169 L[y3]-387.2714+[5]   29020inter-alpha-trypsin R.IYLQPGR.L  423.7452++ L[y5]-570.3358+[1]  638209inhibitor heavy chain H2 P[y3]-329.1932+[2]  235194 Y[b2]-277.1547+[3] 266889 Q[y4]-457.2518+[4]  171389 inter-alpha-trypsin R.LSNENHGIAQR.I 413.5461+++ N[y9]-519.7574++[1]  325409 inhibitor heavy chain H2N[y7]-398.2146++[2]   39521 G[y5]-544.3202+[3]  139598S[b2]-201.1234+[4]   54786 E[y8]-462.7359++[5]   30623inter-alpha-trypsin R.SLAPTAAAKR.R  415.2425++ A[y7]-629.3617+[1] 582421 inhibitor heavy chain H2 L[b2]-201.1234+[2]  430584P[y6]-558.3246+[3]  463815 A[b3]-272.1605+[4]  204183 T[y5]-461.2718+[5]  47301 inter-alpha-trypsin K.EVSFDVELPK.T  581.8032++P[y2]-244.1656+[1]  132304 inhibitor heavy chain H3 V[b2]-229.1183+[2]  48895 L[y3]-357.2496+[3]   20685 inter-alpha-trypsin K.IQENVR.N 379.7114++ E[y4]-517.2729+[1]  190296 inhibitor heavy chain H3E[b3]-371.1925+[2]   51697 Q[b2]-242.1499+[3]   54241 N[y3]-388.2303+[4]  21156 V[y2]-274.1874+[5]    8309 inter-alpha-trypsin R.ALDLSLK.Y 380.2342++ D[y5]-575.3399+[1]  687902 inhibitor heavy chain H3L[b2]-185.1285+[2]  241010 L[y2]-260.1969+[3]   29365inter-alpha-trypsin R.LIQDAVTGLTVN  972.0258++ V[b6]-640.3665+[1] 139259 inhibitor heavy chain H3 GQITGDK.R G[b8]-798.4356+[2]   53886G[y7]-718.3730+[3]   12518 pigment epithelium- K.SSFVAPLEK.S  489.2687++A[y5]-557.3293+[1]   13436 derived factor precursor V[y6]-656.3978+[2]   9350 F[y7]-803.4662+[3]    6672 P[y4]-486.2922+[4]    6753pigment epithelium- K.TVQAVLTVPK.L  528.3266++ Q[y8]-855.5298+[1]  26719 derived factor precursor V[b2]-201.1234+[2]   21239Q[y8]-428.2686++[3]   16900 A[y7]-727.4713+[4]    9518L[y5]-557.3657+[5]    5108 Q[b3]-329.1819+[6]    5450 V[y6]-656.4341+[7]   4391 pigment epithelium- R.ALYYDLISSPDIH  652.6632+++Y[y15]-886.4305++[1]   78073 derived factor precursor GTYK.EY[y14]-804.8988++[2]   26148 pigment epithelium- R.DTDTGALLFIGK.I 625.8350++ G[y8]-818.5135+[1]   25553 derived factor precursorT[b2]-217.0819+[2]   22716 T[b4]-217.0819++[3]   22716L[y5]-577.3708+[4]   11600 I[y3]-317.2183+[5]   11089 A[b6]-561.2151+[6]   6956 pigment epithelium- K.ELLDTVTAPQK.N  607.8350++T[y5]-544.3089+[1]   17139 derived factor precursor D[y8]-859.4520+[2]  17440 L[y9]-972.5360+[3]   14344 A[y4]-443.2613+[4]   11474T[y7]-744.4250+[5]   10808 V[y6]-643.3774+[6]    9064pregnancy-specific beta- K.FQLPGQK.L  409.2320++ L[y5]-542.3297+[1] 116611 1-glycoprotein 1 P[y4]-429.2456+[2]   91769 Q[b2]-276.1343+[3]  93301 pregnancy-specific beta- R.DLYHYITSYVVD  955.4762+++G[y7]-707.3471+[1]    5376 1-glycoprotein 1 GEIIIYGPAYSGR.E Y[y8]-870.4104+[2]    3610 P[y6]-650.3257+[3]    2770 I[y9]-983.4945+[4]   3361 pregnancy-specific beta- K.LFIPQITPK.H  528.8262++ P[y6]-683.4087+[1]   39754 1-glycoprotein 11 F[b2]-261.1598+[2]   29966I[y7]-796.4927+[3]   13162 pregnancy-specific beta- NSATGEESSTSLTIR 776.8761++  E[b7]-689.2737+[1]   11009 1-glycoprotein 11T[y6]-690.4145+[2]   11284 L[y4]-502.3348+[3]    2265S[y7]-389.2269++[4]    1200 T[y3]-389.2507+[5]    1200I[y2]-288.2030+[6]    2248 pregnancy-specific beta- K.FQQSGQNLFIP 617.3317+++  F[y8]-474.2817++[1]   43682 1-glycoprotein 2 QITTK.HG[y12]-680.3852++[2]   24166 S[b4]-491.2249+[3]   23548Q[b3]-404.1928+[4]   17499 I[y4]-462.2922+[5]   17304F[b9]-525.7538++[6]   17206 I[b10]-582.2958++[7]   16718L[b8]-452.2196++[8]   16490 P[y6]-344.2054++[9]   16198G[b5]-548.2463+[10]   15320 pregnancy-specific beta- IHPSYTNYR 575.7856++ N[b7]-813.3890+[1]   16879 1-glycoprotein 2Y[b5]-598.2984+[2]   18087 T[y4]-553.2729+[3]    2682pregnancy-specific beta- FQLSETNR  497.7513++ L[y6]-719.3682+[1]  3580591-glycoprotein 2 S[y5]-606.2842+[2]  182330 Q[b2]-276.1343+[3]  292482pregnancy-specific beta- VSAPSGTGHLPGLNPL  506.2755+++T[b7]-300.6530++[1]   25346 1-glycoprotein 3 H[y8]-860.4989+[2]   12159H[y8]-430.7531++[3]   15522 pregnancy-specific beta- EDAGSYTLHIVK 666.8433++ Y[b6]-623.2307+[1]   23965 1-glycoprotein 3Y[y7]-873.5193+[2]   21686 L[b8]-837.3625+[3]    4104 A[b3]-316.1139+[4]   1987 pregnancy-specific beta- R.TLFIFGVTK.Y  513.3051++F[y7]-811.4713+[1]   62145 1-glycoprotein 4 L[b2]-215.1390+[2]   31687F[y5]-551.3188+[3]     972 pregnancy-specific beta- NYTYIWWLNGQS1097.5576++ W[b6]-841.3879+[1]   25756 1-glycoprotein 4 LPVSPRG[y9]-940.5211+[2]   25018 Y[b4]-542.2245+[3]   19778 Q[y8]-883.4996+[4]   6642 P[y2]-272.1717+[5]    5018 pregnancy-specific beta-GVTGYFTFNLYLK  508.2695+++ L[y2]-260.1969+[1]  176797 1-glycoprotein 5T[y11]-683.8557++[2]  136231 F[b6]-625.2980+[3]   47523L[y4]-536.3443+[4]   23513 pregnancy-specific beta- SNPVTLNVLYGPD 585.6527+++ Y[y7]-817.4203+[1]   14118 1-glycoprotein 6 LPRG[y6]-654.3570+[2]   10433 P[b3]-299.1350+[3]   87138*P[y5]-299.1714++[4]   77478* P[y5]-597.3355+[5]   68089*pregnancy-specific beta- DVLLLVHNLPQNL  791.7741+++ L[y8]-1017.5516+[3] 141169 1-glycoprotein 7 TGHIWYK G[y6]-803.4199+[5]  115905W[y3]-496.2554+[6]  108565 P[y11]-678.8566++[7]  105493V[b2]-215.1026+[1]  239492 L[b3]-328.1867+[2]  204413 N[b8]-904.5251+[4] 121880 pregnancy-specific beta- YGPAYSGR  435.7089++ A[y5]-553.2729+[1]  25743* 1-glycoprotein 7 Y[y4]-482.2358+[2]   25580* P[y6]-650.3257+[3]  10831* S[y3]-319.1724+[4]   10559* G[b2]-221.0921+[5]    7837*pregnancy-specific beta- LQLSETNR  480.7591++ S[b4]-442.2660+[1]   187661-glycoprotein 8 L[b3]-355.2340+[2]   12050 Q[b2]-242.1499+[3]    1339T[b6]-672.3563+[4]    2489 pregnancy-specific beta- K.LFIPQITR.N 494.3029++ P[y5]-614.3620+[1]   53829 1-glycoprotein 9I[y6]-727.4461+[2]   13731 I[b3]-374.2438+[3]    4178 Q[y4]-517.3093+[4]   2984 pregnancy-specific beta- K.LPIPYITINNLNPR.E  819.4723++P[b2]-211.1441+[1]   18814* 1-glycoprotein 9 P[b4]-211.1441++[2]  18814* T[b7]-798.4760+[3]   17287* T[y8]-941.5163+[4]   10205*Y[b5]-584.3443+[5]   10136* N[y6]-727.3846+[6]    9511*pregnancy-specific beta- R.SNPVILNVLYGP  589.6648+++ P[y5]-597.3355+[1]   3994 1-glycoprotein 9 DLPR.I Y[y7]-817.4203+[2]    3743G[y6]-654.3570+[3]    3045 pregnancy-specific beta- DVLLLVHNLPQNL 810.4387+++ P[y7]-960.4614+[1]  120212 1-glycoprotein 9 PGYFWYKV[b2]-215.1026+[2]   65494 L[b3]-328.1867+[3]   54798pregnancy-specific beta- SENYTYIWWLNG  846.7603+++ W[y15]-834.4488++[1]  14788 1-glycoprotein 9 QSLPVSPGVK P[y4]-200.6314++[2]   19000Y[y17]-972.5225++[3]    4596 L[b10]-678.8166++[4]    2660Y[b6]-758.2992+[5]    1705 P[y4]-400.2554+[6]    1847 Pan-PSG ILILPSVTR 506.3317++ P[y5]-559.3198+[1]  484395 L[b2]-227.1754+[2]  102774L[b4]-227.1754++[3]  102774 I[y7]-785.4880+[4]   90153I[b3]-340.2595+[5]   45515 L[y6]-672.4039+[6]   40368 thyroxine-bindingK.AQWANPFDPSK.T  630.8040++ A[b4]-457.2194+[1]   30802globulin precursor S[y2]-234.1448+[2]   28255 D[y4]-446.2245+[3]   24933thyroxine-binding K.AVLHIGEK.G  289.5080+++ I[y4]-446.2609+[1]  220841globulin precursor H[y5]-292.1636++[2]  303815 H[y5]-583.3198+[3] 133795 V[b2]-171.1128+[4]  166139 L[y6]-348.7056++[5]  823533thyroxine-binding K.FLNDVK.T  368.2054++ N[y4]-475.2511+[1]  296859globulin precursor V[y2]-246.1812+[2]  219597 L[b2]-261.1598+[3]   87504thyroxine-binding K.FSISATYDLGATL  800.4351++ Y[y9]-993.5615+[1]   34111globulin precursor LK.M G[y6]-602.3872+[2]   17012 D[y8]-830.4982+  45104 S[b2]-235.1077+[4]   15480 thyroxine-binding K.GWVDLFVPK.F 530.7949++ W[b2]-244.1081+[1] 1261810 globulin precursorP[y2]-244.1656+[2] 1261810 V[b7]-817.4243+[3]  517675 V[y7]-817.4818+[4] 517675 D[y6]-718.4134+[5]  306994 F[b6]-718.3559+[6]  306994V[y3]-343.2340+[7]  112565 V[b3]-343.1765+[8]  112565 thyroxine-bindingK.NALALFVLPK.E  543.3395++ A[y7]-787.5076+[1]  198085 globulin precursorL[b3]-299.1714+[2]  199857 P[y2]-244.1656+[3]  129799 L[y8]-900.5917+[4] 111572 L[y6]-716.4705+[5]   88773 F[y5]-603.3865+[6]   54020L[y3]-357.2496+[7]   43353 thyroxine-binding R.SILFLGK.V  389.2471++L[y5]-577.3708+[1] 1878736 globulin precursor I[b2]-201.1234+[2]  946031G[y2]-204.1343+[3]  424248 L[y3]-317.2183+[4]  291162 F[y4]-464.2867+[5] 391171 AFP R.DFNQFSSGEK.N  386.8402+++ N[b3]-189.0764++[1]   42543S[y4]-210.6081++[2]   21340 G[y3]-333.1769+[3]   53766N[b3]-377.1456+[4]   58644 F[b2]-263.1026+[5]    5301 AFP K.GYQELLEK.C 490.2584++ E[y5]-631.3661+[1]  110518 L[y4]-502.3235+[2]   74844E[y2]-276.1554+[3]   42924 E[b4]-478.1932+[4]   20953 AFP K.GEEELQK.Y 416.7060++ E[b2]-187.0713+[1]   37843 E[y4]-517.2980+[2]   56988 AFPK.FIYEIAR.R  456.2529++ I[y3]-359.2401+[1]   34880 I[b2]-261.1598+[2]   7931 AFP R.HPFLYAPTILL  590.3348+++ I[y7]-421.7660++[1]   11471WAAR.Y L[y6]-365.2239++[2]    5001 A[b6]-365.1896++[3]    5001L[y6]-729.4406+[4]    3218 F[b3]-382.1874+[5]    6536 A[b6]-729.3719+[6]   3218 AFP R.TFQAITVTK.L  504.7898++ T[b6]-662.3508+[1]   11241T[y4]-448.2766+[2]    7541 A[b4]-448.2191+[3]    7541 AFP K.LTTLER.G 366.7162++ T[y4]-518.2933+[1]    7836 L[b4]-215.1390++[2]    4205T[b2]-215.1390+[3]    4205 AFP R.HPQLAVSVILR.V L[y2]-288.2030+[1]   3781 I[y3]-401.2871+[2]    2924 L[b4]-476.2616+[3]    2647 AFPK.LGEYYLQNAFLV  631.6646+++ G[b2]-171.1128+[1]   10790 AYTK.KY[y3]-411.2238+[2]    2303 F[b10]-600.2902++[3]    1780Y[b4]-463.2187+[4]    2214 F[y7]-421.2445++[6]    3072 PGH1 R.ILPSVPK.D 377.2471++ P[y5]-527.3188+[1] 5340492 S[y4]-430.2660+[5]  419777P[y2]-244.1656+[2] 4198508 P[y5]-264.1630++[3] 2771328L[b2]-227.1754+[4] 2331263 PGH1 K.AEHPTWGDEQL  639.3026+++E[b9]-512.2120++[1]   64350 FQTTR.L P[b4]-218.1030++[2]   38282L[b11]-632.7833++[3]  129128 G[y10]-597.7911++[4]   19406G[b7]-779.3471+[5]   51467 T[y3]-189.1108++[6]   10590D[y9]-569.2804++[7]   12460 L[y6]-765.4254+[8]    6704D[b8]-447.6907++[9]    4893 P[b4]-435.1987+[10]    8858Q[y7]-893.4839+[11]    6101 T[b5]-268.6268++[12]    5456T[b5]-536.2463+[13]    5549 PGH1 R.LILIGETIK.I  500.3261++G[y5]-547.3086+[1]    7649 T[y3]-361.2445+[2]    6680 E[y4]-490.2871+[3]   5234 L[y7]-773.4767+[4]    3342 PGH1 R.LQPFNEYR.K  533.7694++N[b5]-600.3140+[1]   25963 F[b4]-486.2711+[2]    6915 E[y3]-467.2249+[3]  15079 *QTRAP5500 data, all other peak areas are from Agilent 6490

Next, the top 2-10 transitions per peptide and up to 7 peptides perprotein were selected for collision energy (CE) optimization on theAgilent 6490. Using Skyline or MassHunter Qual software, the optimizedCE value for each transition was determined based on the peak area orsignal to noise. The two transitions with the largest peak areas perpeptide and at least two peptides per protein were chosen for the finalMRM method. Substitutions of transitions with lower peak areas were madewhen a transition with a larger peak area had a high background level orhad a low m/z value that has more potential for interference.

Lastly, the retention times of selected peptides were mapped using thesame column and gradient as our established sMRM assay. The newlydiscovered analytes were subsequently added to the sMRM method and usedin a further hypothesis-dependent discovery study described in Example 5below.

The above method was typical for most proteins. However, in some cases,the differentially expressed peptide identified in the shotgun methoddid not uniquely identify a protein, for example, in protein familieswith high sequence identity. In these cases, a MRM method was developedfor each family member. Also, let it be noted that, for any givenprotein, peptides in addition to those found to be significant andfragment ions not observed on the Orbitrap may have been included in MRMoptimization and added to the final sMRM method if those yielded thebest signal intensities.

Example 5. Study IV to Identify and Confirm Preterm Birth Biomarkers

A further hypothesis-dependent discovery study was performed with thescheduled MRM assay used in Examples 3 but now augmented with newlydiscovered analytes from the Example 4. Less robust transitions (fromthe original 1708 described in Example 1) were removed to improveanalytical performance and make room for the newly discovered analytes.Samples included approximately 30 cases and 60 matched controls fromeach of three gestational periods (early, 17-22 weeks, middle, 23-25weeks and late, 26-28 weeks). Log transformed peak areas for eachtransition were corrected for run order and batch effects by regression.The ability of each analyte to separate cases and controls wasdetermined by calculating univariate AUC values from ROC curves. Rankedunivariate AUC values (0.6 or greater) are reported for individualgestational age window sample sets (Tables 12, 13, 15) and a combinationof the middle and late window (Table 14). Multivariate classifiers werebuilt using different subsets of analytes (described below) by Lasso andRandom Forest methods. Lasso significant transitions correspond to thosewith non-zero coefficients and Random Forest analyze ranking wasdetermined by the Gini importance values (mean decrease in modelaccuracy if that variable is removed). We report all analytes withnon-zero Lasso coefficients (Tables 16-32) and the top 30 analytes fromeach Random Forest analysis (Tables 33-49). Models were builtconsidering the top univariate 32 or 100 analytes, the single bestunivariate analyte for the top 50 proteins or all analytes. Lastly 1000rounds of bootstrap resampling were performed and the nonzero Lassocoefficients or Random Forest Gini importance values were summed foreach analyte amongst panels with AUCs of 0.85 or greater.

TABLE 12 Early Window Individual Stats Transition Protein AUCELIEELVNITQNQK_557.6_517.3 IL13_HUMAN 0.834 ITLPDFTGDLR_624.3_288.2LBP_HUMAN 0.822 FLNWIK_410.7_560.3 HABP2_HUMAN 0.820ITLPDFTGDLR_624.3_920.5 LBP_HUMAN 0.808 SFRPFVPR_335.9_635.3 LBP_HUMAN0.800 LIQDAVTGLTVNGQITGDK_972.0_ ITIH3_HUMAN 0.800 798.4FSVVYAK_407.2_579.4 FETUA_HUMAN 0.796 ITGFLKPGK_320.9_429.3 LBP_HUMAN0.796 AHYDLR_387.7_288.2 FETUA_HUMAN 0.796 FSVVYAK_407.2_381.2FETUA_HUMAN 0.795 SFRPFVPR_335.9_272.2 LBP_HUMAN 0.795DVLLLVHNLPQNLPGYFWYK_810.4_ PSG9_HUMAN 0.794 967.5ELIEELVNITQNQK_557.6_618.3 IL13_HUMAN 0.794 QALEEFQK_496.8_680.3CO8B_HUMAN 0.792 DAGLSWGSAR_510.3_390.2 NEUR4_HUMAN 0.792AHYDLR_387.7_566.3 FETUA_HUMAN 0.791 VFQFLEK_455.8_811.4 CO5_HUMAN 0.786ITGFLKPGK_320.9_301.2 LBP_HUMAN 0.783 VFQFLEK_455.8_276.2 CO5_HUMAN0.782 SLLQPNK_400.2_599.4 CO8A_HUMAN 0.781 VQTAHFK_277.5_431.2CO8A_HUMAN 0.780 SDLEVAHYK_531.3_617.3 CO8B_HUMAN 0.777SLLQPNK_400.2_358.2 CO8A_HUMAN 0.776 TLLPVSKPEIR_418.3_288.2 CO5_HUMAN0.776 ALNHLPLEYNSALYSR_621.0_538.3 CO6_HUMAN 0.774 DISEVVTPR_508.3_787.4CFAB_HUMAN 0.774 VSEADSSNADWVTK_754.9_533.3 CFAB_HUMAN 0.773LSSPAVITDK_515.8_743.4 PLMN_HUMAN 0.773 VQEAHLTEDQIFYFPK_655.7_701.4CO8G_HUMAN 0.772 DVLLLVHNLPQNLPGYFWYK_810.4_ PSG9_HUMAN 0.771 594.3ALVLELAK_428.8_672.4 INHBE_HUMAN 0.770 FLNWIK_410.7_561.3 HABP2_HUMAN0.770 LSSPAVITDK_515.8_830.5 PLMN_HUMAN 0.769 LPNNVLQEK_527.8_844.5AFAM_HUMAN 0.769 VSEADSSNADWVTK_754.9_347.2 CFAB_HUMAN 0.768HTLNQIDEVK_598.8_951.5 FETUA_HUMAN 0.767 TTSDGGYSFK_531.7_860.4INHA_HUMAN 0.761 YENYTSSFFIR_713.8_756.4 IL12B_HUMAN 0.760HTLNQIDEVK_598.8_958.5 FETUA_HUMAN 0.760 DISEVVTPR_508.3_472.3CFAB_HUMAN 0.760 LIQDAVTGLTVNGQITGDK_972.0_ ITIH3_HUMAN 0.759 640.4EAQLPVIENK_570.8_699.4 PLMN_HUMAN 0.759 SLPVSDSVLSGFEQR_810.9_836.4CO8G_HUMAN 0.757 AVLHIGEK_289.5_348.7 THBG_HUMAN 0.755GLQYAAQEGLLALQSELLR_1037.1_ LBP_HUMAN 0.752 929.5 FLQEQGHR_338.8_497.3CO8G_HUMAN 0.750 LPNNVLQEK_527.8_730.4 AFAM_HUMAN 0.750AVLHIGEK_289.5_292.2 THBG_HUMAN 0.749 QLYGDTGVLGR_589.8_501.3 CO8G_HUMAN0.748 WWGGQPLWITATK_772.4_929.5 ENPP2_HUMAN 0.747 NADYSYSVWK_616.8_769.4CO5_HUMAN 0.746 GLQYAAQEGLLALQSELLR_1037.1_ LBP_HUMAN 0.746 858.5SLPVSDSVLSGFEQR_810.9_723.3 CO8G_HUMAN 0.745 IEEIAAK_387.2_531.3CO5_HUMAN 0.743 TYLHTYESEI_628.3_908.4 ENPP2_HUMAN 0.742WWGGQPLWITATK_772.4_373.2 ENPP2_HUMAN 0.742 FQLSETNR_497.8_605.3PSG2_HUMAN 0.741 NIQSVNVK_451.3_674.4 GROA_HUMAN 0.741TGVAVNKPAEFTVDAK_549.6_258.1 FLNA_HUMAN 0.740 LQGTLPVEAR_542.3_571.3CO5_HUMAN 0.740 SGFSFGFK_438.7_732.4 CO8B_HUMAN 0.740HELTDEELQSLFTNFANVVDK_817.1_ AFAM_HUMAN 0.740 906.5 VQTAHFK_277.5_502.3CO8A_HUMAN 0.739 YENYTSSFFIR_713.8_293.1 IL12B_HUMAN 0.739AFTECCVVASQLR_770.9_574.3 CO5_HUMAN 0.736 EAQLPVIENK_570.8_329.2PLMN_HUMAN 0.734 QALEEFQK_496.8_551.3 CO8B_HUMAN 0.734DAQYAPGYDK_564.3_813.4 CFAB_HUMAN 0.734 TEFLSNYLTNVDDITLVPGTLGR_ENPP2_HUMAN 0.734 846.8_600.3 IAIDLFK_410.3_635.4 HEP2_HUMAN 0.733TASDFITK_441.7_781.4 GELS_HUMAN 0.731 YEFLNGR_449.7_606.3 PLMN_HUMAN0.731 TVQAVLTVPK_528.3_428.3 PEDF_HUMAN 0.731 LIENGYFHPVK_439.6_627.4F13B_HUMAN 0.730 DALSSVQESQVAQQAR_573.0_672.4 APOC3_HUMAN 0.730TVQAVLTVPK_528.3_855.5 PEDF_HUMAN 0.730 ALQDQLVLVAAK_634.9_289.2ANGT_HUMAN 0.727 TYLHTYESEI_628.3_515.3 ENPP2_HUMAN 0.727SDLEVAHYK_531.3_746.4 CO8B_HUMAN 0.726 FLPCENK_454.2_550.2 IL10_HUMAN0.725 HPWIVHWDQLPQYQLNR_744.0_ KS6A3_HUMAN 0.725 1047.0AFTECCVVASQLR_770.9_673.4 CO5_HUMAN 0.725 YGLVTYATYPK_638.3_843.4CFAB_HUMAN 0.724 TLEAQLTPR_514.8_685.4 HEP2_HUMAN 0.724DAQYAPGYDK_564.3_315.1 CFAB_HUMAN 0.724 QGHNSVFLIK_381.6_260.2HEMO_HUMAN 0.722 HELTDEELQSLFTNFANVVDK_817.1_ AFAM_HUMAN 0.722 854.4TLEAQLTPR_514.8_814.4 HEP2_HUMAN 0.721 IEEIAAK_387.2_660.4 CO5_HUMAN0.721 HFQNLGK_422.2_527.2 AFAM_HUMAN 0.721 IAPQLSTEELVSLGEK_857.5_333.2AFAM_HUMAN 0.721 DALSSVQESQVAQQAR_573.0_502.3 APOC3_HUMAN 0.720ALNHLPLEYNSALYSR_621.0_696.4 CO6_HUMAN 0.719 IAIDLFK_410.3_706.4HEP2_HUMAN 0.719 FLQEQGHR_338.8_369.2 CO8G_HUMAN 0.719ALQDQLVLVAAK_634.9_956.6 ANGT_HUMAN 0.718 IEGNLIFDPNNYLPK_874.0_414.2APOB_HUMAN 0.717 YEFLNGR_449.7_293.1 PLMN_HUMAN 0.717TASDFITK_441.7_710.4 GELS_HUMAN 0.716 DADPDTFFAK_563.8_825.4 AFAM_HUMAN0.716 TLLPVSKPEIR_418.3_514.3 CO5_HUMAN 0.716 NADYSYSVWK_616.8_333.2CO5_HUMAN 0.715 YGLVTYATYPK_638.3_334.2 CFAB_HUMAN 0.715VNHVTLSQPK_374.9_459.3 B2MG_HUMAN 0.715 HYGGLTGLNK_530.3_759.4PGAM1_HUMAN 0.714 DFHINLFQVLPWLK_885.5_400.2 CFAB_HUMAN 0.714NCSFSIIYPVVIK_770.4_555.4 CRHBP_HUMAN 0.714 HPWIVHWDQLPQYQLNR_744.0_KS6A3_HUMAN 0.712 918.5 AQPVQVAEGSEPDGFWEALGGK_ GELS_HUMAN 0.711758.0_574.3 ALDLSLK_380.2_185.1 ITIH3_HUMAN 0.711 ALDLSLK_380.2_575.3ITIH3_HUMAN 0.710 LDFHFSSDR_375.2_611.3 INHBC_HUMAN 0.709TLNAYDHR_330.5_312.2 PAR3_HUMAN 0.707 EVFSKPISWEELLQ_852.9_260.2FA40A_HUMAN 0.706 IAPQLSTEELVSLGEK_857.5_533.3 AFAM_HUMAN 0.704LIENGYFHPVK_439.6_343.2 F13B_HUMAN 0.703 NFPSPVDAAFR_610.8_775.4HEMO_HUMAN 0.703 QLYGDTGVLGR_589.8_345.2 CO8G_HUMAN 0.702LYYGDDEK_501.7_563.2 CO8A_HUMAN 0.702 FQLSETNR_497.8_476.3 PSG2_HUMAN0.701 TGVAVNKPAEFTVDAK_549.6_977.5 FLNA_HUMAN 0.700IPGIFELGISSQSDR_809.9_679.3 CO8B_HUMAN 0.700 TLFIFGVTK_513.3_215.1PSG4_HUMAN 0.699 YYGYTGAFR_549.3_450.3 TRFL_HUMAN 0.699QVFAVQR_424.2_473.3 ELNE_HUMAN 0.699 AQPVQVAEGSEPDGFWEALGGK_ GELS_HUMAN0.699 758.0_623.4 DFNQFSSGEK_386.8_189.1 FETA_HUMAN 0.699SVSLPSLDPASAK_636.4_473.3 APOB_HUMAN 0.699 GNGLTWAEK_488.3_634.3C163B_HUMAN 0.698 LYYGDDEK_501.7_726.3 CO8A_HUMAN 0.698NFPSPVDAAFR_610.8_959.5 HEMO_HUMAN 0.698 FAFNLYR_465.8_565.3 HEP2_HUMAN0.697 SGFSFGFK_438.7_585.3 CO8B_HUMAN 0.696 DFHINLFQVLPWLK_885.5_543.3CFAB_HUMAN 0.696 LQGTLPVEAR_542.3_842.5 CO5_HUMAN 0.694GAVHVVVAETDYQSFAVLYLER_ CO8G_HUMAN 0.694 822.8_863.5TSESTGSLPSPFLR_739.9_716.4 PSMG1_HUMAN 0.694 YISPDQLADLYK_713.4_277.2ENOA_HUMAN 0.694 ESDTSYVSLK_564.8_347.2 CRP_HUMAN 0.693ILDDLSPR_464.8_587.3 ITIH4_HUMAN 0.693 VQEAHLTEDQIFYFPK_655.7_CO8G_HUMAN 0.692 391.2 SGVDLADSNQK_567.3_662.3 VGFR3_HUMAN 0.692DTDTGALLFIGK_625.8_217.1 PEDF_HUMAN 0.692 HFQNLGK_422.2_285.1 AFAM_HUMAN0.691 NNQLVAGYLQGPNVNLEEK_700.7_ IL1RA_HUMAN 0.691 999.5IPGIFELGISSQSDR_809.9_849.4 CO8B_HUMAN 0.691 ESDTSYVSLK_564.8_696.4CRP_HUMAN 0.690 GAVHVVVAETDYQSFAVLYLER_ CO8G_HUMAN 0.690 822.8_580.3DADPDTFFAK_563.8_302.1 AFAM_HUMAN 0.690 LDFHFSSDR_375.2_464.2INHBC_HUMAN 0.689 TLFIFGVTK_513.3_811.5 PSG4_HUMAN 0.688DFNQFSSGEK_386.8_333.2 FETA_HUMAN 0.687 IQTHSTTYR_369.5_627.3 F13B_HUMAN0.686 HYFIAAVER_553.3_658.4 FA8_HUMAN 0.686 VNHVTLSQPK_374.9_244.2B2MG_HUMAN 0.686 DLHLSDVFLK_396.2_366.2 CO6_HUMAN 0.685DPTFIPAPIQAK_433.2_556.3 ANGT_HUMAN 0.684 AGITIPR_364.2_272.2 IL17_HUMAN0.684 IAQYYYTFK_598.8_884.4 F13B_HUMAN 0.684 SGVDLADSNQK_567.3_591.3VGFR3_HUMAN 0.683 VEPLYELVTATDFAYSSTVR_754.4_ CO8B_HUMAN 0.682 549.3AGITIPR_364.2_486.3 IL17_HUMAN 0.682 YEVQGEVFTKPQLWP_911.0_293.1CRP_HUMAN 0.681 APLTKPLK_289.9_357.2 CRP_HUMAN 0.681YNSQLLSFVR_613.8_508.3 TFR1_HUMAN 0.681 ANDQYLTAAALHNLDEAVK_686.4_IL1A_HUMAN 0.681 301.1 IQTHSTTYR_369.5_540.3 F13B_HUMAN 0.681IHPSYTNYR_575.8_598.3 PSG2_HUMAN 0.681 TEFLSNYLTNVDDITLVPGTLGR_ENPP2_HUMAN 0.681 846.8_699.4 DPTFIPAPIQAK_433.2_461.2 ANGT_HUMAN 0.679FQSVFTVTR_542.8_623.4 C1QC_HUMAN 0.679 LQVNTPLVGASLLR_741.0_925.6BPIA1_HUMAN 0.679 DEIPHNDIALLK_459.9_510.8 HABP2_HUMAN 0.678HATLSLSIPR_365.6_272.2 VGFR3_HUMAN 0.678 EDTPNSVWEPAK_686.8_315.2C1S_HUMAN 0.678 TGISPLALIK_506.8_741.5 APOB_HUMAN 0.678ILPSVPK_377.2_244.2 PGH1_HUMAN 0.676 HATLSLSIPR_365.6_472.3 VGFR3_HUMAN0.676 QGHNSVFLIK_381.6_520.4 HEMO_HUMAN 0.676 LPATEKPVLLSK_432.6_460.3HYOU1_HUMAN 0.675 APLTKPLK_289.9_398.8 CRP_HUMAN 0.674GVTGYFTFNLYLK_508.3_683.9 PSG5_HUMAN 0.673 TFLTVYWTPER_706.9_401.2ICAM1_HUMAN 0.673 GDTYPAELYITGSILR_885.0_274.1 F13B_HUMAN 0.672EDTPNSVWEPAK_686.8_630.3 C1S_HUMAN 0.672 SLDFTELDVAAEK_719.4_316.2ANGT_HUMAN 0.672 VELAPLPSWQPVGK_760.9_342.2 ICAM1_HUMAN 0.671GPGEDFR_389.2_322.2 PTGDS_HUMAN 0.670 TDAPDLPEENQAR_728.3_843.4CO5_HUMAN 0.670 GVTGYFTFNLYLK_508.3_260.2 PSG5_HUMAN 0.669FAFNLYR_465.8_712.4 HEP2_HUMAN 0.669 ITENDIQIALDDAK_779.9_873.5APOB_HUMAN 0.669 ILNIFGVIK_508.8_790.5 TFR1_HUMAN 0.669ISQGEADINIAFYQR_575.6_684.4 MMP8_HUMAN 0.668 GDTYPAELYITGSILR_885.0_F13B_HUMAN 0.668 1332.8 ELLESYIDGR_597.8_710.4 THRB_HUMAN 0.668FTITAGSK_412.7_576.3 FABPL_HUMAN 0.667 ILDGGNK_358.7_490.2 CXCL5_HUMAN0.667 GWVTDGFSSLK_598.8_854.4 APOC3_HUMAN 0.667FSLVSGWGQLLDR_493.3_403.2 FA7_HUMAN 0.665 IHPSYTNYR_575.8_813.4PSG2_HUMAN 0.665 ELLESYIDGR_597.8_839.4 THRB_HUMAN 0.665SDGAKPGPR_442.7_213.6 COLI_HUMAN 0.664 IAQYYYTFK_598.8_395.2 F13B_HUMAN0.664 SILFLGK_389.2_201.1 THBG_HUMAN 0.664 IEVNESGTVASSSTAVIVSAR_693.0_PAI1_HUMAN 0.664 545.3 VSAPSGTGHLPGLNPL_506.3_300.7 PSG3_HUMAN 0.664LLAPSDSPEWLSFDVTGVVR_730.1_ TGFB1_HUMAN 0.664 430.3YYGYTGAFR_549.3_771.4 TRFL_HUMAN 0.663 TDAPDLPEENQAR_728.3_613.3CO5_HUMAN 0.663 IEVIITLK_464.8_815.5 CXL11_HUMAN 0.662ILPSVPK_377.2_227.2 PGH1_HUMAN 0.662 FGFGGSTDSGPIR_649.3_745.4ADA12_HUMAN 0.661 DYWSTVK_449.7_347.2 APOC3_HUMAN 0.661IEGNLIFDPNNYLPK_874.0_845.5 APOB_HUMAN 0.661 WILTAAHTLYPK_471.9_407.2C1R_HUMAN 0.661 WNFAYWAAHQPWSR_607.3_545.3 PRG2_HUMAN 0.661SILFLGK_389.2_577.4 THBG_HUMAN 0.661 FSLVSGWGQLLDR_493.3_516.3 FA7_HUMAN0.661 DTDTGALLFIGK_625.8_818.5 PEDF_HUMAN 0.661 SEYGAALAWEK_612.8_845.5CO6_HUMAN 0.660 LWAYLTIQELLAK_781.5_371.2 ITIH1_HUMAN 0.660LLEVPEGR_456.8_356.2 C1S_HUMAN 0.659 ITENDIQIALDDAK_779.9_632.3APOB_HUMAN 0.659 LTTVDIVTLR_565.8_716.4 IL2RB_HUMAN 0.658IEVIITLK_464.8_587.4 CXL11_HUMAN 0.658 QLGLPGPPDVPDHAAYHPF_676.7_ITIH4_HUMAN 0.658 299.2 TLAFVR_353.7_492.3 FA7_HUMAN 0.656NSDQEIDFK_548.3_294.2 S10A5_HUMAN 0.656 YHFEALADTGISSEFYDNANDLLSK_CO8A_HUMAN 0.656 940.8_874.5 SEPRPGVLLR_375.2_454.3 FA7_HUMAN 0.655FLPCENK_454.2_390.2 IL10_HUMAN 0.654 NCSFSIIYPVVIK_770.4_831.5CRHBP_HUMAN 0.654 SLDFTELDVAAEK_719.4_874.5 ANGT_HUMAN 0.654ILLLGTAVESAWGDEQSAFR_721.7_ CXA1_HUMAN 0.653 909.4SVSLPSLDPASAK_636.4_885.5 APOB_HUMAN 0.653 TGISPLALIK_506.8_654.5APOB_HUMAN 0.653 YNQLLR_403.7_288.2 ENOA_HUMAN 0.653YEVQGEVFTKPQLWP_911.0_392.2 CRP_HUMAN 0.652 VPGLYYFTYHASSR_554.3_720.3C1QB_HUMAN 0.650 SLQNASAIESILK_687.4_589.4 IL3_HUMAN 0.650WILTAAHTLYPK_471.9_621.4 C1R_HUMAN 0.650 GWVTDGFSSLK_598.8_953.5APOC3_HUMAN 0.650 YGIEEHGK_311.5_599.3 CXA1_HUMAN 0.649QDLGWK_373.7_503.3 TGFB3_HUMAN 0.649 DYWSTVK_449.7_620.3 APOC3_HUMAN0.648 ALVLELAK_428.8_331.2 INHBE_HUMAN 0.647 QLGLPGPPDVPDHAAYHPF_676.7_ITIH4_HUMAN 0.646 263.1 SEYGAALAWEK_612.8_788.4 CO6_HUMAN 0.645TFLTVYWTPER_706.9_502.3 ICAM1_HUMAN 0.644 FQSVFTVTR_542.8_722.4C1QC_HUMAN 0.643 DPNGLPPEAQK_583.3_669.4 RET4_HUMAN 0.642ETLLQDFR_511.3_322.2 AMBP_HUMAN 0.642 IIEVEEEQEDPYLNDR_996.0_777.4FBLN1_HUMAN 0.641 ELCLDPK_437.7_359.2 IL8_HUMAN 0.641TPSAAYLWVGTGASEAEK_919.5_ GELS_HUMAN 0.641 849.4 NQSPVLEPVGR_598.3_866.5KS6A3_HUMAN 0.641 FNAVLTNPQGDYDTSTGK_964.5_ C1QC_HUMAN 0.641 333.2LLEVPEGR_456.8_686.4 C1S_HUMAN 0.641 FFQYDTWK_567.8_840.4 IGF2_HUMAN0.640 SPEAEDPLGVER_649.8_670.4 Z512B_HUMAN 0.639 SEPRPGVLLR_375.2_654.4FA7_HUMAN 0.639 SGAQATWTELPWPHEK_613.3_793.4 HEMO_HUMAN 0.638YSHYNER_323.5_581.3 HABP2_HUMAN 0.638 YHFEALADTGISSEFYDNANDLLSK_CO8A_HUMAN 0.637 940.8_301.1 DLHLSDVFLK_396.2_260.2 CO6_HUMAN 0.637YSHYNER_323.5_418.2 HABP2_HUMAN 0.637 YYLQGAK_421.7_327.1 ITIH4_HUMAN0.636 EVPLSALTNILSAQLISHWK_740.8_ PAI1_HUMAN 0.636 996.6VPGLYYFTYHASSR_554.3_420.2 C1QB_HUMAN 0.636AALAAFNAQNNGSNFQLEEISR_789.1_ FETUA_HUMAN 0.636 746.4ETLLQDFR_511.3_565.3 AMBP_HUMAN 0.635 IVLSLDVPIGLLQILLEQAR_735.1_UCN2_HUMAN 0.635 503.3 ENPAVIDFELAPIVDLVR_670.7_ CO6_HUMAN 0.635 811.5LQLSETNR_480.8_355.2 PSG8_HUMAN 0.635 DPDQTDGLGLSYLSSHIANVER_796.4_GELS_HUMAN 0.635 456.2 NVNQSLLELHK_432.2_656.3 FRIH_HUMAN 0.634EIGELYLPK_531.3_633.4 AACT_HUMAN 0.634 SPEQQETVLDGNLIIR_906.5_699.3ITIH4_HUMAN 0.634 NKPGVYTDVAYYLAWIR_677.0_ FA12_HUMAN 0.632 545.3QNYHQDSEAAINR_515.9_544.3 FRIH_HUMAN 0.632 EKPAGGIPVLGSLVNTVLK_631.4_BPIB1_HUMAN 0.632 930.6 VTFEYR_407.7_614.3 CRHBP_HUMAN 0.630DLPHITVDR_533.3_490.3 MMP7_HUMAN 0.630 VEHSDLSFSK_383.5_234.1 B2MG_HUMAN0.630 ENPAVIDFELAPIVDLVR_670.7_ CO6_HUMAN 0.630 601.4YGFYTHVFR_397.2_659.4 THRB_HUMAN 0.629 ILDDLSPR_464.8_702.3 ITIH4_HUMAN0.629 DPNGLPPEAQK_583.3_497.2 RET4_HUMAN 0.629GSLVQASEANLQAAQDFVR_668.7_ ITIH1_HUMAN 0.629 806.4 FLYHK_354.2_447.2AMBP_HUMAN 0.627 FNAVLTNPQGDYDTSTGK_964.5_ C1QC_HUMAN 0.627 262.1LQDAGVYR_461.2_680.3 PD1L1_HUMAN 0.627 INPASLDK_429.2_630.4 C163A_HUMAN0.626 LEEHYELR_363.5_580.3 PAI2_HUMAN 0.625 VEHSDLSFSK_383.5_468.2B2MG_HUMAN 0.624 TSDQIHFFFAK_447.6_659.4 ANT3_HUMAN 0.624ATLSAAPSNPR_542.8_570.3 CXCL2_HUMAN 0.624 YGFYTHVFR_397.2_421.3THRB_HUMAN 0.624 EANQSTLENFLER_775.9_678.4 IL4_HUMAN 0.623GQQPADVTGTALPR_705.9_314.2 CSF1_HUMAN 0.623 VELAPLPSWQPVGK_760.9_400.3ICAM1_HUMAN 0.622 GEVTYTTSQVSK_650.3_750.4 EGLN_HUMAN 0.622SLQAFVAVAAR_566.8_487.3 IL23A_HUMAN 0.622 HYGGLTGLNK_530.3_301.1PGAM1_HUMAN 0.622 GPEDQDISISFAWDK_854.4_753.4 DEF4_HUMAN 0.622YVVISQGLDKPR_458.9_400.3 LRP1_HUMAN 0.621 LWAYLTIQELLAK_781.5_300.2ITIH1_HUMAN 0.621 SGAQATWTELPWPHEK_613.3_510.3 HEMO_HUMAN 0.621GTAEWLSFDVTDTVR_848.9_952.5 TGFB3_HUMAN 0.621 FFQYDTWK_567.8_712.3IGF2_HUMAN 0.621 AHQLAIDTYQEFEETYIPK_766.0_ CSH_HUMAN 0.620 634.4LPATEKPVLLSK_432.6_347.2 HYOU1_HUMAN 0.620 NIQSVNVK_451.3_546.3GROA_HUMAN 0.620 TAVTANLDIR_537.3_288.2 CHL1_HUMAN 0.619WSAGLTSSQVDLYIPK_883.0_515.3 CBG_HUMAN 0.616 QINSYVK_426.2_496.3CBG_HUMAN 0.616 GFQALGDAADIR_617.3_288.2 TIMP1_HUMAN 0.615WNFAYWAAHQPWSR_607.3_673.3 PRG2_HUMAN 0.615 NEIWYR_440.7_357.2FA12_HUMAN 0.615 VLEPTLK_400.3_587.3 VTDB_HUMAN 0.614YYLQGAK_421.7_516.3 ITIH4_HUMAN 0.614 ALNSIIDVYHK_424.9_774.4S10A8_HUMAN 0.614 ETPEGAEAKPWYEPIYLGGVFQLEK_ TNFA_HUMAN 0.614951.1_877.5 LNIGYIEDLK_589.3_837.4 PAI2_HUMAN 0.614NVNQSLLELHK_432.2_543.3 FRIH_HUMAN 0.613 ILLLGTAVESAWGDEQSAFR_721.7_CXA1_HUMAN 0.613 910.6 AALAAFNAQNNGSNFQLEEISR_789.1_ FETUA_HUMAN 0.613633.3 VLEPTLK_400.3_458.3 VTDB_HUMAN 0.613 VGEYSLYIGR_578.8_708.4SAMP_HUMAN 0.613 DIPHWLNPTR_416.9_373.2 PAPP1_HUMAN 0.612NEIVFPAGILQAPFYTR_968.5_ ECE1_HUMAN 0.612 357.2AEHPTWGDEQLFQTTR_639.3_765.4 PGH1_HUMAN 0.612VEPLYELVTATDFAYSSTVR_754.4_ CO8B_HUMAN 0.611 712.4DEIPHNDIALLK_459.9_260.2 HABP2_HUMAN 0.611 QINSYVK_426.2_610.3 CBG_HUMAN0.610 SWNEPLYHLVTEVR_581.6_614.3 PRL_HUMAN 0.610 YGIEEHGK_311.5_341.2CXA1_HUMAN 0.610 FGFGGSTDSGPIR_649.3_946.5 ADA12_HUMAN 0.610ANDQYLTAAALHNLDEAVK_686.4_ IL1A_HUMAN 0.610 317.2 VRPQQLVK_484.3_609.4ITIH4_HUMAN 0.609 IPKPEASFSPR_410.2_506.3 ITIH4_HUMAN 0.609SPEQQETVLDGNLIIR_906.5_685.4 ITIH4_HUMAN 0.609 DDLYVSDAFHK_655.3_704.3ANT3_HUMAN 0.609 ELPEHTVK_476.8_347.2 VTDB_HUMAN 0.609 FLYHK_354.2_284.2AMBP_HUMAN 0.608 QRPPDLDTSSNAVDLLFFTDESGDSR_ C1R_HUMAN 0.608 961.5_262.2DPDQTDGLGLSYLSSHIANVER_796.4_ GELS_HUMAN 0.608 328.1 NEIWYR_440.7_637.4FA12_HUMAN 0.607 LQLSETNR_480.8_672.4 PSG8_HUMAN 0.606GQVPENEANVVITTLK_571.3_462.3 CADH1_HUMAN 0.606 FTGSQPFGQGVEHATANK_626.0_TSP1_HUMAN 0.605 521.2 LEPLYSASGPGLRPLVIK_637.4_ CAA60698 0.605 260.2QRPPDLDTSSNAVDLLFFTDESGDSR_ C1R_HUMAN 0.604 961.5_866.3LTTVDIVTLR_565.8_815.5 IL2RB_HUMAN 0.604 TSDQIHFFFAK_447.6_512.3ANT3_HUMAN 0.604 IQHPFTVEEFVLPK_562.0_861.5 PZP_HUMAN 0.603NKPGVYTDVAYYLAWIR_677.0_ FA12_HUMAN 0.603 821.5 TEQAAVAR_423.2_615.4FA12_HUMAN 0.603 EIGELYLPK_531.3_819.5 AACT_HUMAN 0.602LFYADHPFIFLVR_546.6_647.4 SERPH_HUMAN 0.602 AEHPTWGDEQLFQTTR_639.3_569.3PGH1_HUMAN 0.601 TSYQVYSK_488.2_787.4 C163A_HUMAN 0.601YTTEIIK_434.2_704.4 C1R_HUMAN 0.601 NVIQISNDLENLR_509.9_402.3 LEP_HUMAN0.600 AFLEVNEEGSEAAASTAVVIAGR_ ANT3_HUMAN 0.600 764.4_685.4

TABLE 13 Middle Window Individual Stats Transition Protein AUCSEYGAALAWEK_612.8_788.4 CO6_HUMAN 0.738 VFQFLEK_455.8_811.4 CO5_HUMAN0.709 ALNHLPLEYNSALYSR_621.0_696.4 CO6_HUMAN 0.705SLDFTELDVAAEK_719.4_316.2 ANGT_HUMAN 0.692 VEHSDLSFSK_383.5_234.1B2MG_HUMAN 0.686 LLAPSDSPEWLSFDVTGVVR_730.1_ TGFB1_HUMAN 0.683 430.3ALNHLPLEYNSALYSR_621.0_538.3 CO6_HUMAN 0.683 VLEPTLK_400.3_458.3VTDB_HUMAN 0.681 LHEAFSPVSYQHDLALLR_699.4_ FA12_HUMAN 0.681 251.2SEYGAALAWEK_612.8_845.5 CO6_HUMAN 0.679 YGIEEHGK_311.5_599.3 CXA1_HUMAN0.677 ALQDQLVLVAAK_634.9_289.2 ANGT_HUMAN 0.675 VLEPTLK_400.3_587.3VTDB_HUMAN 0.667 VNHVTLSQPK_374.9_244.2 B2MG_HUMAN 0.665IEEIAAK_387.2_660.4 CO5_HUMAN 0.664 DALSSVQESQVAQQAR_573.0_502.3APOC3_HUMAN 0.664 TLLPVSKPEIR_418.3_514.3 CO5_HUMAN 0.662ALQDQLVLVAAK_634.9_956.6 ANGT_HUMAN 0.661 TLAFVR_353.7_492.3 FA7_HUMAN0.661 SEPRPGVLLR_375.2_654.4 FA7_HUMAN 0.658 VEHSDLSFSK_383.5_468.2B2MG_HUMAN 0.653 DPTFIPAPIQAK_433.2_461.2 ANGT_HUMAN 0.653QGHNSVFLIK_381.6_260.2 HEMO_HUMAN 0.650 SLDFTELDVAAEK_719.4_874.5ANGT_HUMAN 0.650 ELPQSIVYK_538.8_417.7 FBLN3_HUMAN 0.649TYLHTYESEI_628.3_515.3 ENPP2_HUMAN 0.647 SLQAFVAVAAR_566.8_804.5IL23A_HUMAN 0.646 AQPVQVAEGSEPDGFWEALGGK_ GELS_HUMAN 0.644 758.0_574.3QGHNSVFLIK_381.6_520.4 HEMO_HUMAN 0.644 VNHVTLSQPK_374.9_459.3B2MG_HUMAN 0.643 DLHLSDVFLK_396.2_260.2 CO6_HUMAN 0.643TEQAAVAR_423.2_615.4 FA12_HUMAN 0.643 GPITSAAELNDPQSILLR_632.4_EGLN_HUMAN 0.643 826.5 HFQNLGK_422.2_527.2 AFAM_HUMAN 0.642TEQAAVAR_423.2_487.3 FA12_HUMAN 0.642 AVDIPGLEAATPYR_736.9_399.2TENA_HUMAN 0.642 TLFIFGVTK_513.3_811.5 PSG4_HUMAN 0.642DLHLSDVFLK_396.2_366.2 CO6_HUMAN 0.641 AFTECCVVASQLR_770.9_574.3CO5_HUMAN 0.640 EVFSKPISWEELLQ_852.9_376.2 FA40A_HUMAN 0.639DPTFIPAPIQAK_433.2_556.3 ANGT_HUMAN 0.639 FSLVSGWGQLLDR_493.3_403.2FA7_HUMAN 0.638 HYINLITR_515.3_301.1 NPY_HUMAN 0.637 HFQNLGK_422.2_285.1AFAM_HUMAN 0.637 VPLALFALNR_557.3_620.4 PEPD_HUMAN 0.636IHPSYTNYR_575.8_813.4 PSG2_HUMAN 0.635 IEEIAAK_387.2_531.3 CO5_HUMAN0.635 GEVTYTTSQVSK_650.3_750.4 EGLN_HUMAN 0.634 DFNQFSSGEK_386.8_333.2FETA_HUMAN 0.634 VVGGLVALR_442.3_784.5 FA12_HUMAN 0.634SDGAKPGPR_442.7_459.2 COLI_HUMAN 0.634 DVLLLVHNLPQNLTGHIWYK_791.8_PSG7_HUMAN 0.634 310.2 TLLPVSKPEIR_418.3_288.2 CO5_HUMAN 0.633NKPGVYTDVAYYLAWIR_677.0_ FA12_HUMAN 0.630 821.5 QVFAVQR_424.2_473.3ELNE_HUMAN 0.630 NHYTESISVAK_624.8_415.2 NEUR1_HUMAN 0.630IAPQLSTEELVSLGEK_857.5_333.2 AFAM_HUMAN 0.629 IHPSYTNYR_575.8_598.3PSG2_HUMAN 0.627 EVFSKPISWEELLQ_852.9_260.2 FA40A_HUMAN 0.627SILFLGK_389.2_201.1 THBG_HUMAN 0.626 IEVIITLK_464.8_587.4 CXL11_HUMAN0.625 VVGGLVALR_442.3_685.4 FA12_HUMAN 0.624 VVLSSGSGPGLDLPLVLGLPLQLK_SHBG_HUMAN 0.624 791.5_598.4 FGFGGSTDSGPIR_649.3_946.5 ADA12_HUMAN 0.623VVLSSGSGPGLDLPLVLGLPLQLK_ SHBG_HUMAN 0.622 791.5_768.5YGIEEHGK_311.5_341.2 CXA1_HUMAN 0.621 LHEAFSPVSYQHDLALLR_699.4_FA12_HUMAN 0.621 380.2 AHYDLR_387.7_566.3 FETUA_HUMAN 0.620FSVVYAK_407.2_381.2 FETUA_HUMAN 0.618 ALALPPLGLAPLLNLWAKPQGR_ SHBG_HUMAN0.618 770.5_256.2 YENYTSSFFIR_713.8_293.1 IL12B_HUMAN 0.617VELAPLPSWQPVGK_760.9_342.2 ICAM1_HUMAN 0.617 SILFLGK_389.2_577.4THBG_HUMAN 0.616 ILPSVPK_377.2_227.2 PGH1_HUMAN 0.615IPSNPSHR_303.2_496.3 FBLN3_HUMAN 0.615 HYFIAAVER_553.3_301.1 FA8_HUMAN0.615 FSVVYAK_407.2_579.4 FETUA_HUMAN 0.613 VFQFLEK_455.8_276.2CO5_HUMAN 0.613 IAPQLSTEELVSLGEK_857.5_533.3 AFAM_HUMAN 0.613ILPSVPK_377.2_244.2 PGH1_HUMAN 0.613 NKPGVYTDVAYYLAWIR_677.0_ FA12_HUMAN0.613 545.3 WSAGLTSSQVDLYIPK_883.0_515.3 CBG_HUMAN 0.612TPSAAYLWVGTGASEAEK_919.5_ GELS_HUMAN 0.612 849.4 ALALPPLGLAPLLNLWAKPQGR_SHBG_HUMAN 0.612 770.5_457.3 QLGLPGPPDVPDHAAYHPF_676.7_ ITIH4_HUMAN0.612 299.2 ILDDLSPR_464.8_587.3 ITIH4_HUMAN 0.611VELAPLPSWQPVGK_760.9_400.3 ICAM1_HUMAN 0.611 DADPDTFFAK_563.8_825.4AFAM_HUMAN 0.611 NHYTESISVAK_624.8_252.1 NEUR1_HUMAN 0.611SEPRPGVLLR_375.2_454.3 FA7_HUMAN 0.611 LNIGYIEDLK_589.3_950.5 PAI2_HUMAN0.611 ANLINNIFELAGLGK_793.9_299.2 LCAP_HUMAN 0.609LTTVDIVTLR_565.8_716.4 IL2RB_HUMAN 0.608 TQILEWAAER_608.8_761.4EGLN_HUMAN 0.608 NEPEETPSIEK_636.8_573.3 SOX5_HUMAN 0.608AQPVQVAEGSEPDGFWEALGGK_ GELS_HUMAN 0.607 758.0_623.4LQVNTPLVGASLLR_741.0_925.6 BPIA1_HUMAN 0.607 VPSHAVVAR_312.5_345.2TRFL_HUMAN 0.607 SLCINASAIESILK_687.4_860.5 IL3_HUMAN 0.607GVTGYFTFNLYLK_508.3_260.2 PSG5_HUMAN 0.605 DFNQFSSGEK_386.8_189.1FETA_HUMAN 0.605 QLGLPGPPDVPDHAAYHPF_676.7_ ITIH4_HUMAN 0.605 263.1TLEAQLTPR_514.8_814.4 HEP2_HUMAN 0.604 AFTECCVVASQLR_770.9_673.4CO5_HUMAN 0.604 LTTVDIVTLR_565.8_815.5 IL2RB_HUMAN 0.604TLNAYDHR_330.5_312.2 PAR3_HUMAN 0.603 LWAYLTIQELLAK_781.5_300.2ITIH1_HUMAN 0.603 GGLFADIASHPWQAAIFAK_667.4_ TPA_HUMAN 0.603 375.2IPSNPSHR_303.2_610.3 FBLN3_HUMAN 0.603 TDAPDLPEENQAR_728.3_843.4CO5_HUMAN 0.603 SPQAFYR_434.7_684.4 REL3_HUMAN 0.602SSNNPHSPIVEEFQVPYNK_729.4_ C1S_HUMAN 0.601 261.2 AHYDLR_387.7_288.2FETUA_HUMAN 0.600 DGSPDVTTADIGANTPDATK_973.5_ PGRP2_HUMAN 0.600 844.4SPQAFYR_434.7_556.3 REL3_HUMAN 0.600

TABLE 14 Middle Late Individual Stats Transition Protein AUCALNHLPLEYNSALYSR_621.0_696.4 CO6_HUMAN 0.656 VPLALFALNR_557.3_620.4PEPD_HUMAN 0.655 ALNHLPLEYNSALYSR_621.0_538.3 CO6_HUMAN 0.652AVYEAVLR_460.8_587.4 PEPD_HUMAN 0.649 SEPRPGVLLR_375.2_654.4 FA7_HUMAN0.644 VFQFLEK_455.8_811.4 CO5_HUMAN 0.643AQPVQVAEGSEPDGFWEALGGK_758.0_574.3 GELS_HUMAN 0.640 TLAFVR_353.7_492.3FA7_HUMAN 0.639 TEQAAVAR_423.2_615.4 FA12_HUMAN 0.637YGIEEHGK_311.5_599.3 CXA1_HUMAN 0.637 TEQAAVAR_423.2_487.3 FA12_HUMAN0.633 QINSYVK_426.2_496.3 CBG_HUMAN 0.633 LIEIANHVDK_384.6_683.4ADA12_HUMAN 0.633 SEYGAALAWEK_612.8_845.5 CO6_HUMAN 0.633ALQDQLVLVAAK_634.9_956.6 ANGT_HUMAN 0.628 VLEPTLK_400.3_587.3 VTDB_HUMAN0.628 DFNQFSSGEK_386.8_333.2 FETA_HUMAN 0.628 TYLHTYESEI_628.3_515.3ENPP2_HUMAN 0.628 LIEIANHVDK_384.6_498.3 ADA12_HUMAN 0.626QINSYVK_426.2_610.3 CBG_HUMAN 0.625 SLDFTELDVAAEK_719.4_316.2 ANGT_HUMAN0.625 DPTFIPAPIQAK_433.2_461.2 ANGT_HUMAN 0.625 AVYEAVLR_460.8_750.4PEPD_HUMAN 0.623 YENYTSSFFIR_713.8_756.4 IL12B_HUMAN 0.623SEYGAALAWEK_612.8_788.4 CO6_HUMAN 0.623 WSAGLTSSQVDLYIPK_883.0_515.3CBG_HUMAN 0.622 DALSSVQESQVAQQAR_573.0_502.3 APOC3_HUMAN 0.622ALQDQLVLVAAK_634.9_289.2 ANGT_HUMAN 0.621 SLQAFVAVAAR_566.8_804.5IL23A_HUMAN 0.621 DPTFIPAPIQAK_433.2_556.3 ANGT_HUMAN 0.620FGFGGSTDSGPIR_649.3_946.5 ADA12_HUMAN 0.619 VLEPTLK_400.3_458.3VTDB_HUMAN 0.619 SLDFTELDVAAEK_719.4_874.5 ANGT_HUMAN 0.618EVFSKPISWEELLQ_852.9_376.2 FA40A_HUMAN 0.618 FGFGGSTDSGPIR_649.3_745.4ADA12_HUMAN 0.618 TPSAAYLWVGTGASEAEK_919.5_849.4 GELS_HUMAN 0.615LHEAFSPVSYQHDLALLR_699.4_251.2 FA12_HUMAN 0.615 TLEAQLTPR_514.8_685.4HEP2_HUMAN 0.613 ELPQSIVYK_538.8_417.7 FBLN3_HUMAN 0.612GYQELLEK_490.3_631.4 FETA_HUMAN 0.612 VPLALFALNR_557.3_917.6 PEPD_HUMAN0.611 DLHLSDVFLK_396.2_260.2 CO6_HUMAN 0.611 LTTVDIVTLR_565.8_815.5IL2RB_HUMAN 0.608 WSAGLTSSQVDLYIPK_883.0_357.2 CBG_HUMAN 0.608ITQDAQLK_458.8_702.4 CBG_HUMAN 0.608 NIQSVNVK_451.3_674.4 GROA_HUMAN0.607 ALEQDLPVNIK_620.4_570.4 CNDP1_HUMAN 0.607 TLNAYDHR_330.5_312.2PAR3_HUMAN 0.606 LWAYLTIQELLAK_781.5_300.2 ITIH1_HUMAN 0.606VVGGLVALR_442.3_784.5 FA12_HUMAN 0.605AQPVQVAEGSEPDGFWEALGGK_758.0_623.4 GELS_HUMAN 0.603SVVLIPLGAVDDGEHSCINEK_703.0_798.4 CNDP1_HUMAN 0.603SETEIHQGFQHLHQLFAK_717.4_318.1 CBG_HUMAN 0.603LLAPSDSPEWLSFDVTGVVR_730.1_430.3 TGFB1_HUMAN 0.603 IEVIITLK_464.8_587.4CXL11_HUMAN 0.602 ITQDAQLK_458.8_803.4 CBG_HUMAN 0.602AEIEYLEK_497.8_552.3 LYAM1_HUMAN 0.601 AVDIPGLEAATPYR_736.9_399.2TENA_HUMAN 0.601 LTTVDIVTLR_565.8_716.4 IL2RB_HUMAN 0.600WWGGQPLWITATK_772.4_929.5 ENPP2_HUMAN 0.600

TABLE 15 Late Window Individual Stats Transition Protein AUCAVYEAVLR_460.8_587.4 PEPD_HUMAN 0.724 AEIEYLEK_497.8_552.3 LYAM1_HUMAN0.703 QINSYVK_426.2_496.3 CBG_HUMAN 0.695 AVYEAVLR_460.8_750.4PEPD_HUMAN 0.693 AALAAFNAQNNGSNFQLEEISR_ FETUA_HUMAN 0.684 789.1_746.4QINSYVK_426.2_610.3 CBG_HUMAN 0.681 VPLALFALNR_557.3_620.4 PEPD_HUMAN0.678 VGVISFAQK_474.8_580.3 TFR2_HUMAN 0.674TGVAVNKPAEFTVDAK_549.6_258.1 FLNA_HUMAN 0.670 LIEIANHVDK_384.6_683.4ADA12_HUMAN 0.670 LIEIANHVDK_384.6_498.3 ADA12_HUMAN 0.660SGVDLADSNQK_567.3_662.3 VGFR3_HUMAN 0.660 TSYQVYSK_488.2_787.4C163A_HUMAN 0.657 ITQDAQLK_458.8_702.4 CBG_HUMAN 0.652YYGYTGAFR_549.3_450.3 TRFL_HUMAN 0.650 ALEQDLPVNIK_620.4_798.5CNDP1_HUMAN 0.650 VFQYIDLHQDEFVQTLK_708.4_375.2 CNDP1_HUMAN 0.650SGVDLADSNQK_567.3_591.3 VGFR3_HUMAN 0.648 YENYTSSFFIR_713.8_756.4IL12B_HUMAN 0.647 VLSSIEQK_452.3_691.4 1433S_HUMAN 0.647YSHYNER_323.5_418.2 HABP2_HUMAN 0.646 ILDGGNK_358.7_603.3 CXCL5_HUMAN0.645 GTYLYNDCPGPGQDTDCR_697.0_666.3 TNR1A_HUMAN 0.645AEIEYLEK_497.8_389.2 LYAM1_HUMAN 0.645 TLPFSR_360.7_506.3 LYAM1_HUMAN0.645 DEIPHNDIALLK_459.9_510.8 HABP2_HUMAN 0.644 ALEQDLPVNIK_620.4_570.4CNDP1_HUMAN 0.644 SPEAEDPLGVER_649.8_314.1 Z512B_HUMAN 0.644FGFGGSTDSGPIR_649.3_745.4 ADA12_HUMAN 0.642 TASDFITK_441.7_781.4GELS_HUMAN 0.641 SETEIHQGFQHLHQLFAK_717.4_447.2 CBG_HUMAN 0.640SPQAFYR_434.7_556.3 REL3_HUMAN 0.639 TAVTANLDIR_537.3_288.2 CHL1_HUMAN0.636 VPLALFALNR_557.3_917.6 PEPD_HUMAN 0.636 YISPDQLADLYK_713.4_277.2ENOA_HUMAN 0.633 SETEIHQGFQHLHQLFAK_717.4_318.1 CBG_HUMAN 0.633SEPRPGVLLR_375.2_654.4 FA7_HUMAN 0.633 GYQELLEK_490.3_631.4 FETA_HUMAN0.633 AYSDLSR_406.2_375.2 SAMP_HUMAN 0.633 SVVLIPLGAVDDGEHSCINEK_CNDP1_HUMAN 0.632 703.0_798.4 TLEAQLTPR_514.8_685.4 HEP2_HUMAN 0.631WSAGLTSSQVDLYIPK_883.0_515.3 CBG_HUMAN 0.631 TEQAAVAR_423.2_615.4FA12_HUMAN 0.628 AQPVQVAEGSEPDGFWEALGGK_ GELS_HUMAN 0.626 758.0_574.3AGITIPR_364.2_486.3 IL17_HUMAN 0.626 AEVIWTSSDHQVLSGK_586.3_300.2PD1L1_HUMAN 0.625 TEQAAVAR_423.2_487.3 FA12_HUMAN 0.625NHYTESISVAK_624.8_415.2 NEUR1_HUMAN 0.625 WSAGLTSSQVDLYIPK_883.0_357.2CBG_HUMAN 0.623 YSHYNER_323.5_581.3 HABP2_HUMAN 0.623DFNQFSSGEK_386.8_333.2 FETA_HUMAN 0.621 NIQSVNVK_451.3_674.4 GROA_HUMAN0.620 SVVLIPLGAVDDGEHSCINEK_ CNDP1_HUMAN 0.620 703.0_286.2TLAFVR_353.7_492.3 FA7_HUMAN 0.619 AVDIPGLEAATPYR_736.9_286.1 TENA_HUMAN0.619 TEFLSNYLTNVDDITLVPGTLGR_ ENPP2_HUMAN 0.618 846.8_600.3YWGVASFLQK_599.8_849.5 RET4_HUMAN 0.618 TPSAAYLWVGTGASEAEK_919.5_428.2GELS_HUMAN 0.618 DPNGLPPEAQK_583.3_669.4 RET4_HUMAN 0.617TYLHTYESEI_628.3_908.4 ENPP2_HUMAN 0.616 SPQAFYR_434.7_684.4 REL3_HUMAN0.616 TPSAAYLWVGTGASEAEK_919.5_849.4 GELS_HUMAN 0.615ALNHLPLEYNSALYSR_621.0_538.3 C06_HUMAN 0.615 IEVNESGTVASSSTAVIVSAR_PAI1_HUMAN 0.615 693.0_545.3 LTTVDIVTLR_565.8_815.5 IL2RB_HUMAN 0.615LWAYLTIQELLAK_781.5_371.2 ITIH1_HUMAN 0.613 SYTITGLQPGTDYK_772.4_352.2FINC_HUMAN 0.612 GAVHVVVAETDYQSFAVLYLER_ CO8G_HUMAN 0.612 822.8_863.5FQLPGQK_409.2_276.1 PSG1_HUMAN 0.612 ILDGGNK_358.7_490.2 CXCL5_HUMAN0.611 DYWSTVK_449.7_620.3 APOC3_HUMAN 0.611 AGLLRPDYALLGHR_518.0_595.4PGRP2_HUMAN 0.611 ALNFGGIGVVVGHELTHAFDDQGR_ ECE1_HUMAN 0.611 837.1_360.2GYQELLEK_490.3_502.3 FETA_HUMAN 0.611 HATLSLSIPR_365.6_472.3 VGFR3_HUMAN0.610 SVPVTKPVPVTKPITVTK_631.1_658.4 Z512B_HUMAN 0.610FQLPGQK_409.2_429.2 PSG1_HUMAN 0.610 IYLQPGR_423.7_329.2 ITIH2_HUMAN0.610 TLNAYDHR_330.5_312.2 PAR3_HUMAN 0.609 DPNGLPPEAQK_583.3_497.2RET4_HUMAN 0.609 FGFGGSTDSGPIR_649.3_946.5 ADA12_HUMAN 0.609TYLHTYESEI_628.3_515.3 ENPP2_HUMAN 0.608 GAVHVVVAETDYQSFAVLYLER_CO8G_HUMAN 0.608 822.8_580.3 VPSHAVVAR_312.5_515.3 TRFL_HUMAN 0.608YWGVASFLQK_599.8_350.2 RET4_HUMAN 0.608 EWVAIESDSVQPVPR_856.4_468.3CNDP1_HUMAN 0.607 LQDAGVYR_461.2_680.3 PD1L1_HUMAN 0.607DLYHYITSYVVDGEIIIYGPAYSGR_ PSG1_HUMAN 0.607 955.5_650.3LWAYLTIQELLAK_781.5_300.2 ITIH1_HUMAN 0.606 ITENDIQIALDDAK_779.9_632.3APOB_HUMAN 0.606 SYTITGLQPGTDYK_772.4_680.3 FINC_HUMAN 0.606FFQYDTWK_567.8_712.3 IGF2_HUMAN 0.605 IYLQPGR_423.7_570.3 ITIH2_HUMAN0.605 YNCILLR_403.7_529.4 ENOA_HUMAN 0.605 WWGGQPLWITATK_772.4_929.5ENPP2_HUMAN 0.605 WWGGQPLWITATK_772.4_373.2 ENPP2_HUMAN 0.605TASDFITK_441.7_710.4 GELS_HUMAN 0.605 EWVAIESDSVQPVPR_856.4_486.2CNDP1_HUMAN 0.605 YEFLNGR_449.7_606.3 PLMN_HUMAN 0.604SNPVTLNVLYGPDLPR_585.7_654.4 PSG6_HUMAN 0.604 ITQDAQLK_458.8_803.4CBG_HUMAN 0.603 LTTVDIVTLR_565.8_716.4 IL2RB_HUMAN 0.602FNAVLTNPQGDYDTSTGK_ C1QC_HUMAN 0.602 964.5_262.1 ITGFLKPGK_320.9_301.2LBP_HUMAN 0.601 DYWSTVK_449.7_347.2 APOC3_HUMAN 0.601DPTFIPAPIQAK_433.2_556.3 ANGT_HUMAN 0.601 GWVTDGFSSLK_598.8_953.5APOC3_HUMAN 0.601 YYGYTGAFR_549.3_771.4 TRFL_HUMAN 0.601ELPEHTVK_476.8_347.2 VTDB_HUMAN 0.601 FTFTLHLETPKPSISSSNLNPR_ PSG1_HUMAN0.601 829.4_874.4 DLYHYITSYVVDGEIIIYGPAYSGR_ PSG1_HUMAN 0.601955.5_707.3 SPQAFYR_434.7_684.4 REL3_HUMAN 0.616 TPSAAYLWVGTGASEAEK_GELS_HUMAN 0.615 919.5_849.4 ALNHLPLEYNSALYSR_621.0_538.3 CO6_HUMAN0.615 IEVNESGTVASSSTAVIVSAR_ PAI1_HUMAN 0.615 693.0_545.3LTTVDIVTLR_565.8_815.5 IL2RB_HUMAN 0.615 LWAYLTIQELLAK_781.5_371.2ITIH1_HUMAN 0.613 SYTITGLQPGTDYK_772.4_352.2 FINC_HUMAN 0.612GAVHVVVAETDYQSFAVLYLER_ CO8G_HUMAN 0.612 822.8_863.5 FQLPGQK_409.2_276.1PSG1_HUMAN 0.612 DLYHYITSYVVDGEIIIYGPAYSGR_ PSG1_HUMAN 0.601 955.5_707.3

TABLE 16 Lasso Early 32 Coef- Variable Protein ficientLIQDAVTGLTVNGQITGDK_972.0_798.4 ITIH3_HUMAN 9.53 VQTAHFK_277.5_431.2CO8A_HUMAN 9.09 FLNWIK_410.7_560.3 HABP2_HUMAN 6.15ITGFLKPGK_320.9_429.3 LBP_HUMAN 5.29 ELIEELVNITQNQK_557.6_517.3IL13_HUMAN 3.83 ALNHLPLEYNSALYSR_621.0_538.3 CO6_HUMAN 3.41DISEVVTPR_508.3_787.4 CFAB_HUMAN 0.44 AHYDLR_387.7_288.2 FETUA_HUMAN 0.1

TABLE 17 Lasso Early 100 Coef- Variable Protein ficientLIQDAVTGLTVNGQITGDK_ ITIH3_HUMAN 6.56 972.0_798.4 ALNHLPLEYNSALYSR_CO6_HUMAN 6.51 621.0_538.3 VQTAHFK_277.5_431.2 CO8A_HUMAN 4.51NIQSVNVK_451.3_674.4 GROA_HUMAN 3.12 TYLHTYESEI_628.3_908.4 ENPP2_HUMAN2.68 LIENGYFHPVK_439.6_627.4 F13B_HUMAN 2.56 AVLHIGEK_289.5_292.2THBG_HUMAN 2.11 FLNWIK_410.7_560.3 HABP2_HUMAN 1.85ITGFLKPGK_320.9_429.3 LBP_HUMAN 1.36 DALSSVQESQVAQQAR_ APOC3_HUMAN 1.3573.0_672.4 DALSSVQESQVAQQAR_ APOC3_HUMAN 0.83 573.0_502.3FLPCENK_454.2_550.2 IL10_HUMAN 0.39 ELIEELVNITQNQK_557.6_517.3IL13_HUMAN 0.3 TEFLSNYLTNVDDITLVPGTLGR_ ENPP2_HUMAN 0.29 846.8_600.3VSEADSSNADWVTK_754.9_347.2 CFAB_HUMAN 0.27 ITLPDFTGDLR_624.3_288.2LBP_HUMAN 0.13 TGVAVNKPAEFTVDAK_ FLNA_HUMAN 0.04 549.6_258.1TASDFITK_441.7_781.4 GELS_HUMAN −5.91 LIQDAVTGLTVNGQITGDK_ ITIH3_HUMAN6.56 972.0_798.4

TABLE 18 Lasso Protein Early Window Coef- Variable Protein ficientALNHLPLEYNSALYSR_ CO6_HUMAN 7.17 621.0_538.3 LIQDAVTGLTVNGQITGDK_ITIH3_HUMAN 6.06 972.0_798.4 LIENGYFHPVK_439.6_627.4 F13B_HUMAN 3.23WWGGQPLWITATK_772.4_929.5 ENPP2_HUMAN 2.8 QALEEFQK_496.8_680.3CO8B_HUMAN 2.73 NIQSVNVK_451.3_674.4 GROA_HUMAN 2.53 DALSSVQESQVAQQAR_APOC3_HUMAN 2.51 573.0_672.4 AVLHIGEK_289.5_348.7 THBG_HUMAN 2.33FLNWIK_410.7_560.3 HABP2_HUMAN 1.05 FLPCENK_454.2_550.2 IL10_HUMAN 0.74ITLPDFTGDLR_624.3_288.2 LBP_HUMAN 0.7 DISEVVTPR_508.3_787.4 CFAB_HUMAN0.45 EVFSKPISWEELLQ_852.9_260.2 FA40A_HUMAN 0.17 YYGYTGAFR_549.3_450.3TRFL_HUMAN 0.06 TASDFITK_441.7_781.4 GELS_HUMAN −7.65

TABLE 19 Lasso All Early Window Coef- Variable Protein ficientFLNWIK_410.7_560.3 HABP2_HUMAN 3.74 AHYDLR_387.7_288.2 FETUA_HUMAN 0.07ALNHLPLEYNSALYSR_ CO6_HUMAN 6.07 621.0_538.3 LIQDAVTGLTVNGQITGDK_ITIH3_HUMAN 8.85 972.0_798.4 TYLHTYESEI_628.3_908.4 ENPP2_HUMAN 2.97VQTAHFK_277.5_431.2 CO8A_HUMAN 3.36 ELIEELVNITQNQK_557.6_618.3IL13_HUMAN 11.24 VSEADSSNADWVTK_754.9_347.2 CFAB_HUMAN 0.63AVLHIGEK_289.5_292.2 THBG_HUMAN 0.51 TGVAVNKPAEFTVDAK_ FLNA_HUMAN 0.17549.6_977.5 LIENGYFHPVK_439.6_343.2 F13B_HUMAN 1.7AQPVQVAEGSEPDGFWEALGGK_ GELS_HUMAN −0.93 758.0_574.3YYGYTGAFR_549.3_450.3 TRFL_HUMAN 1.4 TASDFITK_441.7_781.4 GELS_HUMAN−0.07 NIQSVNVK_451.3_674.4 GROA_HUMAN 2.12 DALSSVQESQVAQQAR_ APOC3_HUMAN1.15 573.0_672.4 DALSSVQESQVAQQAR_ APOC3_HUMAN 0.09 573.0_502.3FGFGGSTDSGPIR_649.3_745.4 ADA12_HUMAN 2.45 ALDLSLK_380.2_575.3ITIH3_HUMAN 2.51 TLFIFGVTK_513.3_811.5 PSG4_HUMAN 4.12ISQGEADINIAFYQR_575.6_684.4 MMP8_HUMAN 1.29 SGVDLADSNQK_567.3_591.3VGFR3_HUMAN 0.55 GPGEDFR_389.2_322.2 PTGDS_HUMAN 0.07DPNGLPPEAQK_583.3_669.4 RET4_HUMAN 1.36 WNFAYWAAHQPWSR_607.3_545.3PRG2_HUMAN −1.27 ELCLDPK_437.7_359.2 IL8_HUMAN 0.3 FFQYDTWK_567.8_840.4IGF2_HUMAN 1.83 IIEVEEEQEDPYLNDR_ FBLN1_HUMAN 1.14 996.0_777.4ECEELEEK_533.2_405.2 IL15_HUMAN 1.78 LEEHYELR_363.5_580.3 PAI2_HUMAN0.15 LNIGYIEDLK_589.3_837.4 PAI2_HUMAN 0.32 TAVTANLDIR_537.3_288.2CHL1_HUMAN −0.98 SWNEPLYHLVTEVR_581.6_716.4 PRL_HUMAN 1.88ILNIFGVIK_508.8_790.5 TFR1_HUMAN 0.05 TPSAAYLWVGTGASEAEK_ GELS_HUMAN−2.69 919.5_849.4 VGVISFAQK_474.8_693.4 TFR2_HUMAN −5.68LNIGYIEDLK_589.3_950.5 PAI2_HUMAN −1.43 GQVPENEANVVITTLK_571.3_462.3CADH1_HUMAN −0.55 STPSLTTK_417.7_549.3 IL6RA_HUMAN −0.59ALLLGWVPTR_563.3_373.2 PAR4_HUMAN −0.97

TABLE 20 Lasso SummedCoef Early Window SumBest Transition Protein CoefsLIQDAVTGLTVNGQITGDK_ ITIH3_HUMAN 1173.723955 972.0_798.4ALNHLPLEYNSALYSR_ CO6_HUMAN 811.0150364 621.0_538.3 ELIEELVNITQNQK_IL13_HUMAN 621.9659363 557.6_618.3 VQTAHFK_277.5_431.2 CO8A_HUMAN454.178544 NIQSVNVK_451.3_674.4 GROA_HUMAN 355.9550674 TLFIFGVTK_PSG4_HUMAN 331.8629189 513.3_811.5 GPGEDFR_389.2_322.2 PTGDS_HUMAN305.9079494 FLPCENK_454.2_550.2 IL10_HUMAN 296.9473975FLNWIK_410.7_560.3 HABP2_HUMAN 282.9841332 LIENGYFHPVK_ F13B_HUMAN237.5320227 439.6_627.4 ECEELEEK_533.2_405.2 IL15_HUMAN 200.38281FGFGGSTDSGPIR_ ADA12_HUMAN 194.6252869 649.3_745.4 QALEEFQK_496.8_680.3CO8B_HUMAN 179.2518843 IIEVEEEQEDPYLNDR_ FBLN1_HUMAN 177.7534111996.0_777.4 TYLHTYESEI_ ENPP2_HUMAN 164.9735228 628.3_908.4ELIEELVNITQNQK_ IL13_HUMAN 162.2414693 557.6_517.3 LEEHYELR_363.5_580.3PAI2_HUMAN 152.9262386 ISQGEADINIAFYQR_ MMP8_HUMAN 144.2445011575.6_684.4 HPWIVHWDQLPQYQLNR_ KS6A3_HUMAN 140.2287926 744.0_918.5AHYDLR_387.7_288.2 FETUA_HUMAN 137.9737525 GFQALGDAADIR_ TIMP1_HUMAN130.4945567 617.3_288.2 SWNEPLYHLVTEVR_ PRL_HUMAN 127.442646 581.6_716.4SGVDLADSNQK_ VGFR3_HUMAN 120.5149446 567.3_591.3 YENYTSSFFIR_IL12B_HUMAN 117.0947487 713.8_293.1 FFQYDTWK_567.8_840.4 IGF2_HUMAN109.8569617 HYFIAAVER_ FA8_HUMAN 106.9426543 553.3_658.4 ITGFLKPGK_LBP_HUMAN 103.8056505 320.9_429.3 DALSSVQESQVAQQAR_ APOC3_HUMAN98.50490812 573.0_502.3 SGVDLADSNQK_ VGFR3_HUMAN 97.19989285 567.3_662.3ALDLSLK_380.2_575.3 ITIH3_HUMAN 94.84900337 TGVAVNKPAEFTVDAK_ FLNA_HUMAN92.52335783 549.6_258.1 HPWIVHWDQLPQYQLNR_ KS6A3_HUMAN 91.77547608744.0_1047.0 LIQDAVTGLTVNGQITGDK_ ITIH3_HUMAN 83.6483639 972.0_640.4LNIGYIEDLK_ PAI2_HUMAN 83.50221521 589.3_837.4 IALGGLLFPASNLR_SHBG_HUMAN 79.33146741 481.3_657.4 LPATEKPVLLSK_ HYOU1_HUMAN 78.89429168432.6_460.3 FQLSETNR_497.8_605.3 PSG2_HUMAN 78.13445824NEIVFPAGILQAPFYTR_ ECE1_HUMAN 75.12145257 968.5_357.2ALDLSLK_380.2_185.1 ITIH3_HUMAN 63.05454715 DLHLSDVFLK_ CO6_HUMAN58.26831142 396.2_366.2 TQILEWAAER_ EGLN_HUMAN 57.29461621 608.8_761.4FSVVYAK_407.2_381.2 FETUA_HUMAN 54.78436389 VSEADSSNADWVTK_ CFAB_HUMAN54.40003244 754.9_347.2 DPNGLPPEAQK_ RET4_HUMAN 53.89169348 583.3_669.4VQEAHLTEDQIFYFPK_ CO8G_HUMAN 53.33747599 655.7_701.4 LSSPAVITDK_PLMN_HUMAN 53.22513181 515.8_830.5 ITLPDFTGDLR_ LBP_HUMAN 51.5477235624.3_288.2 AVLHIGEK_ THBG_HUMAN 49.73092632 289.5_292.2 GEVTYTTSQVSK_EGLN_HUMAN 45.14743629 650.3_750.4 GYVIIKPLVWV_ SAMP_HUMAN 44.05164273643.9_854.6 TGVAVNKPAEFTVDAK_ FLNA_HUMAN 42.99898046 549.6_977.5YYGYTGAFR_ TRFL_HUMAN 42.90897411 549.3_450.3 ILDGGNK_358.7_490.2CXCL5_HUMAN 42.60771281 FLPCENK_454.2_390.2 IL10_HUMAN 42.56799651GFQALGDAADIR_ TIMP1_HUMAN 38.68456017 617.3_717.4 SDGAKPGPR_ COLI_HUMAN38.47800265 442.7_213.6 NTGVISVVTTGLDR_ CADH1_HUMAN 32.62953675716.4_662.4 SERPPIFEIR_ LRP1_HUMAN 31.48248968 415.2_288.2DFHINLFQVLPWLK_ CFAB_HUMAN 31.27286268 885.5_400.2 DALSSVQESQVAQQAR_APOC3_HUMAN 31.26972354 573.0_672.4 ELCLDPK_ IL8_HUMAN 29.91108737437.7_359.2 ILNIFGVIK_ TFR1_HUMAN 29.88784921 508.8_790.5TEFLSNYLTNVDDITLVPGT ENPP2_HUMAN 29.42327998 LGR_846.8_600.3GAVHVVVAETDYQSFAVLYL CO8G_HUMAN 26.70286929 ER_822.8_863.5AVLHIGEK_289.5_348.7 THBG_HUMAN 25.78703299 TFLTVYWTPER_ ICAM1_HUMAN24.73090242 706.9_401.2 AGITIPR_364.2_486.3 IL17_HUMAN 23.84580477GAVHVVVAETDYQSFAVLYL CO8G_HUMAN 23.81167843 ER_822.8_580.3 SLQAFVAVAAR_IL23A_HUMAN 23.61468839 566.8_487.3 SWNEPLYHLVTEVR_ PRL_HUMAN 23.2538221581.6_614.3 TYLHTYESEI_ ENPP2_HUMAN 22.70115313 628.3_515.3TAHISGLPPSTDFIVYLSGL TENA_HUMAN 22.42695892 APSIR_871.5_800.5QNYHQDSEAAINR_ FRIH_HUMAN 21.96827269 515.9_544.3 AHQLAIDTYQEFEETYIPK_CSH_HUMAN 21.75765717 766.0_634.4 GDTYPAELYITGSILR_ F13B_HUMAN20.89751398 885.0_274.1 AHYDLR_387.7_566.3 FETUA_HUMAN 20.67629529IALGGLLFPASNLR_ SHBG_HUMAN 19.28973033 481.3_412.3 ATNATLDPR_ PAR1_HUMAN18.77604574 479.8_272.2 FSVVYAK_407.2_579.4 FETUA_HUMAN 17.81136564HTLNQIDEVK_ FETUA_HUMAN 17.29763288 598.8_951.5 DIPHWLNPTR_ PAPP1_HUMAN17.00562521 416.9_373.2 LYYGDDEK_ CO8A_HUMAN 16.78897272 501.7_563.2AALAAFNAQNNGSNFQLEE FETUA_HUMAN 16.41986569 ISR_789.1_633.3 IQTHSTTYR_F13B_HUMAN 15.78335174 369.5_627.3 GPITSAAELNDPQSILLR_ EGLN_HUMAN15.3936876 632.4_826.5 QTLSWTVTPK_ PZP_HUMAN 14.92509259 580.8_818.4AVGYLITGYQR_ PZP_HUMAN 13.9795325 620.8_737.4 DIIKPDPPK_ IL12B_HUMAN13.76508282 511.8_342.2 YNCILLR_403.7_288.2 ENOA_HUMAN 12.61733711GNGLTWAEK_ C163B_HUMAN 12.5891421 488.3_634.3 QVFAVQR_424.2_473.3ELNE_HUMAN 12.57709327 FLQEQGHR_ CO8G_HUMAN 12.51843475 338.8_497.3HVVQLR_376.2_515.3 IL6RA_HUMAN 11.83747559 DVLLLVHNLPQNLTGHIW PSG7_HUMAN11.69074708 YK_791.8_883.0 TFLTVYWTPER_ ICAM1_HUMAN 11.63709776706.9_502.3 VELAPLPSWQPVGK_ ICAM1_HUMAN 10.79897269 760.9_400.3TLFIFGVTK_ PSG4_HUMAN 10.2831751 513.3_215.1 AYSDLSR_406.2_375.2SAMP_HUMAN 10.00461148 HATLSLSIPR_ VGFR3_HUMAN 9.967933028 365.6_472.3LQGTLPVEAR_ CO5_HUMAN 9.963760572 542.3_571.3 NTVISVNPSTK_ VCAM1_HUMAN9.124228658 580.3_732.4 EVFSKPISWEELLQ_ FA40A-HUMAN 8.527980294852.9_260.2 SLCINASAIESILK_ IL3_HUMAN 8.429061621 687.4_860.5IQHPFTVEEFVLPK_ PZP_HUMAN 7.996504258 562.0_861.5 GVTGYFTFNLYLK_PSG5_HUMAN 7.94396229 508.3_683.9 VFQYIDLHQDEFVQTLK_ CNDP1_HUMAN7.860590049 708.4_361.2 ILDDLSPR_464.8_587.3 ITIH4_HUMAN 7.593889262LIENGYFHPVK_ F13B_HUMAN 7.05838337 439.6_343.2 VFQFLEK_455.8_811.4CO5_HUMAN 6.976884759 AFTECCVVASQLR_ CO5_HUMAN 6.847474286 770.9_574.3WWGGQPLWITATK_ ENPP2_HUMAN 6.744837357 772.4_929.5 IQTHSTTYR_ F13B_HUMAN6.71464509 369.5_540.3 IAQYYYTFK_ F13B_HUMAN 6.540497911 598.8_395.2YGFYTHVFR_ THRB_HUMAN 6.326347548 397.2_421.3 YHFEALADTGISSEFYDNANCO8A_HUMAN 6.261787525 DLLSK_940.8_874.5 ANDQYLTAAALHNLDEAVK_ IL1A_HUMAN6.217191651 686.4_301.1 FSLVSGWGQLLDR_ FA7-HUMAN 6.1038295 493.3_403.2GWVTDGFSSLK_ APOC3_HUMAN 6.053494609 598.8_854.4 TLEAQLTPR_514.8_814.4HEP2_HUMAN 5.855967278 VSAPSGTGHLPGLNPL_ PSG3_HUMAN 5.625944609506.3_300.7 EAQLPVIENK_ PLMN_HUMAN 5.407703773 570.8_699.4 SPEAEDPLGVER_Z512B_HUMAN 5.341420139 649.8_670.4 IAIDLFK_410.3_635.4 HEP2_HUMAN4.698739039 YEFLNGR_449.7_293.1 PLMN_HUMAN 4.658286706VQTAHFK_277.5_502.3 CO8A_HUMAN 4.628247194 IEVIITLK_464.8_815.5CXL11_HUMAN 4.57198762 ILTPEVR_414.3_601.3 GDF15_HUMAN 4.452884608LEEHYELR_363.5_288.2 PAI2_HUMAN 4.411983862 HATLSLSIPR_ VGFR3_HUMAN4.334242077 365.6_272.2 NSDQEIDFK_ S10A5_HUMAN 4.25302369 548.3_294.2LPNNVLQEK_ AFAM-HUMAN 4.183602548 527.8_844.5 ELANTIK_394.7_475.3S10AC_HUMAN 4.13558153 LSIPQITTK_ PSG5_HUMAN 3.966238797 500.8_687.4TLNAYDHR_ PAR3_HUMAN 3.961140111 330.5_312.2 WWGGQPLWITATK_ ENPP2_HUMAN3.941476057 772.4_373.2 ELLESYIDGR_ THRB_HUMAN 3.832723338 597.8_710.4ATLSAAPSNPR_ CXCL2_HUMAN 3.82834767 542.8_570.3 VVLSSGSGPGLDLPLVLGLPSHBG_HUMAN 3.80737887 LQLK_791.5_598.4 NADYSYSVWK_ CO5_HUMAN 3.56404167616.8_333.2 ILILPSVTR_ PSGx_HUMAN 3.526998593 506.3_559.3 ALEQDLPVNIK_CNDP1_HUMAN 3.410412424 620.4_798.5 QVCADPSEEWVQK_ CCL3_HUMAN 3.30795151788.4_275.2 SVCINDSQAIAEVLNQLK_ DESP_HUMAN 3.259270741 619.7_914.5QVFAVQR_424.2_620.4 ELNE_HUMAN 3.211482663 ALPGEQQPLHALTR_ IBP1_HUMAN3.211207158 511.0_807.5 LEPLYSASGPGLRPLVIK_ CAA60698 3.203088951637.4_260.2 GTYLYNDCPGPGQDTDCR_ TNR1A_HUMAN 3.139418139 697.0_666.3DAGLSWGSAR_ NEUR4_HUMAN 3.005197927 510.2_576.3 YGFYTHVFR_ THRB_HUMAN2.985663918 397.2_659.4 NNQLVAGYLQGPNVNLEEK_ IL1RA_HUMAN 2.866983196700.7_357.2 EKPAGGIPVLGSLVNTVLK_ BPIB1_HUMAN 2.798965142 631.4_930.6FGSDDEGR_441.7_735.3 PTHR_HUMAN 2.743283546 IEVNESGTVASSSTAVIVSAR_PAI1_HUMAN 2.699725572 693.0_545.3 FATTFYQHLADSK_ ANT3_HUMAN 2.615073729510.3_533.3 DYWSTVK_449.7_347.2 APOC3_HUMAN 2.525459346QLGLPGPPDVPDHAAYHPF_ ITIH4_HUMAN 2.525383799 676.7_263.1 LSSPAVITDK_PLMN_HUMAN 2.522306831 515.8_743.4 TEFLSNYLTNVDDITLVPG ENPP2_HUMAN2.473366805 TLGR_846.8_699.4 SILFLGK_389.2_201.1 THBG_HUMAN 2.472413913VTFEYR_407.7_614.3 CRHBP_HUMAN 2.425338167 SVVLIPLGAVDDGEHSCINCNDP1_HUMAN 2.421340244 EK_703.0_798.4 HTLNQIDEVK_ FETUA_HUMAN2.419851187 598.8_958.5 ALNSIIDVYHK_ S10A8_HUMAN 2.367904596 424.9_661.3ETLALLSTHR_ IL5_HUMAN 2.230076769 570.8_500.3 GLQYAAQEGLLALQSELLR_LBP_HUMAN 2.205949216 1037.1_858.5 TYNVDK_370.2_262.1 PPB1_HUMAN2.11849772 FTITAGSK_412.7_576.3 FABPL_HUMAN 2.098589805 GIVEECCFR_IGF2_HUMAN 2.059942995 585.3_900.3 YGIEEHGK_ CXA1_HUMAN 2.033828589311.5_599.3 ALVLELAK_ INHBE_HUMAN 1.993820617 428.8_331.2 ITLPDFTGDLR_LBP_HUMAN 1.968753183 624.3_920.5 HELTDEELQSLFTNFANVV AFAM_HUMAN1.916438806 DK_817.1_906.5 EANQSTLENFLER_ IL4_HUMAN 1.902033355775.9_678.4 DADPDTFFAK_ AFAM_HUMAN 1.882254674 563.8_825.4 LFIPQITR_PSG9_HUMAN 1.860649392 494.3_727.4 DPNGLPPEAQK_ RET4_HUMAN 1.847702127583.3_497.2 VEPLYELVTATDFAYSSTV CO8B_HUMAN 1.842159131 R_754.4_549.3FQLSETNR_497.8_476.3 PSG2_HUMAN 1.834693717 FSLVSGWGQLLDR_ FA7_HUMAN1.790582748 493.3_516.3 NKPGVYTDVAYYLAWIR_ FA12_HUMAN 1.777303353677.0_545.3 FTGSQPFGQGVEHATANK_ TSP1_HUMAN 1.736517431 626.0_521.2DDLYVSDAFHK_ ANT3_HUMAN 1.717534082 655.3_704.3 AFLEVNEEGSEAAASTAVVIANT3_HUMAN 1.679420475 AGR_764.4_685.4 LPNNVLQEK_ AFAM_HUMAN 1.66321148527.8_730.4 IVLSLDVPIGLLQILLEQA UCN2_HUMAN 1.644983604 R_735.1_503.3DPTFIPAPIQAK_ ANGT_HUMAN 1.625411496 433.2_556.3 SDLEVAHYK_ CO8B_HUMAN1.543640117 531.3_617.3 QLYGDTGVLGR_ CO8G_HUMAN 1.505242962 589.8_501.3VNHVTLSQPK_ B2MG_HUMAN 1.48233058 374.9_459.3 TLLPVSKPEIR_ CO5_HUMAN1.439531341 418.3_288.2 SEYGAALAWEK_ CO6_HUMAN 1.424401638 612.8_845.5YGIEEHGK_311.5_341.2 CXA1_HUMAN 1.379872204 DAGLSWGSAR_ NEUR4_HUMAN1.334272677 510.3_390.2 AEHPTWGDEQLFQTTR_ PGH1_HUMAN 1.30549273639.3_569.3 FQSVFTVTR_ C1QC_HUMAN 1.302847429 542.8_623.4VPGLYYFTYHASSR_ C1QB_HUMAN 1.245565877 554.3_420.2 AYSDLSR_406.2_577.3SAMP_HUMAN 1.220777002 ALEQDLPVNIK_ CNDP1_HUMAN 1.216612522 620.4_570.4NAVVQGLEQPHGLVVHPLR_ LRP1_HUMAN 1.212935735 688.4_890.6 TSDQIHFFFAK_ANT3_HUMAN 1.176238265 447.6_659.4 GTYLYNDCPGPGQDTDCR_ TNR1A_HUMAN1.1455649 697.0_335.2 TSYQVYSK_488.2_787.4 C163A_HUMAN 1.048896429ALNSIIDVYHK_ S10A8_HUMAN 1.028522516 424.9_774.4 VELAPLPSWQPVGK_ICAM1_HUMAN 0.995831393 760.9_342.2 LSETNR_360.2_330.2 PSG1_HUMAN0.976094717 HFQNLGK_422.2_527.2 AFAM_HUMAN 0.956286531 ELPQSIVYK_FBLN3_HUMAN 0.947931674 538.8_417.7 LPATEKPVLLSK_ HYOU1_HUMAN0.932537153 432.6_347.2 SPEAEDPLGVER_ Z512B_HUMAN 0.905955419649.8_314.1 DEIPHNDIALLK_ HABP2_HUMAN 0.9032484 459.9_510.8FFQYDTWK_567.8_712.3 IGF2_HUMAN 0.884340285 LIEIANHVDK_ ADA12_HUMAN0.881493383 384.6_498.3 AGFAGDDAPR_ ACTB_HUMAN 0.814836556 488.7_701.3YEFLNGR_449.7_606.3 PLMN_HUMAN 0.767373087 VIAVNEVGR_ CHL1_HUMAN0.721519592 478.8_284.2 SLSQQIENIR_ CO1A1_HUMAN 0.712051082 594.3_531.3EWVAIESDSVQPVPR_ CNDP1_HUMAN 0.647712421 856.4_486.2 YGLVTYATYPK_CFAB_HUMAN 0.618499569 638.3_843.4 SVVLIPLGAVDDGEHSCINE CNDP1_HUMAN0.606626346 K_703.0_286.2 NSDQEIDFK_ S10A5_HUMAN 0.601928175 548.3_409.2NVNQSLLELHK_ FRIH_HUMAN 0.572008792 432.2_543.3 IAQYYYTFK_5 F13B_HUMAN0.495062844 98.8_884.4 GPITSAAELNDPQSILLR_ EGLN_HUMAN 0.47565795632.4_601.4 YTTEIIK_434.2_704.4 C1R_HUMAN 0.433318952 GYVIIKPLVWV_SAMP_HUMAN 0.427905264 643.9_304.2 LDFHFSSDR_ INHBC_HUMAN 0.411898116375.2_464.2 IPSNPSHR_ FBLN3_HUMAN 0.390037291 303.2_496.3 APLTKPLK_CRP_HUMAN 0.38859469 289.9_357.2 EVFSKPISWEELLQ_ FA40A_HUMAN 0.371359974852.9_376.2 YENYTSSFFIR_ IL12B_HUMAN 0.346336267 713.8_756.4SPQAFYR_434.7_556.3 REL3_HUMAN 0.345901234 SVDEALR_395.2_488.3PRDX2_HUMAN 0.307518869 FVFGTTPEDILR_ TSP1_HUMAN 0.302313589 697.9_742.4FTFTLHLETPKPSISSSNLN PSG1_HUMAN 0.269826678 PR_829.4_787.4 VGEYSLYIGR_SAMP_HUMAN 0.226573173 578.8_708.4 ILPSVPK_377.2_244.2 PGH1_HUMAN0.225429414 LFIPQITR_494.3_614.4 PSG9_HUMAN 0.18285533 TGYYFDGISR_FBLN1_HUMAN 0.182474114 589.8_857.4 HYGGLTGLNK_ PGAM1_HUMAN 0.152397007530.3_759.4 NQSPVLEPVGR_ KS6A3_HUMAN 0.128963949 598.3_866.5 IGKPAPDFK_PRDX2_HUMAN 0.113383235 324.9_294.2 TSESTGSLPSPFLR_ PSMG1_HUMAN0.108159874 739.9_716.4 ESDTSYVSLK_ CRP_HUMAN 0.08569303 564.8_347.2ETPEGAEAKPWYEPIYLGGV TNFA_HUMAN 0.039781728 FQLEK_951.1_877.5TSDQIHFFFAK_ ANT3_HUMAN 0.008064465 447.6_512.3

TABLE 21 Lasso32 Middle Window Coef- Variable UniProt_ID ficientSEYGAALAWEK_612.8_788.4 CO6_HUMAN 6.99 VFQFLEK_455.8_811.4 CO5_HUMAN6.43 VLEPTLK_400.3_458.3 VTDB_HUMAN 3.99 SLDFTELDVAAEK_719.4_316.2ANGT_HUMAN 3.33 TLAFVR_353.7_492.3 FA7_HUMAN 2.44 YGIEEHGK_311.5_599.3CXA1_HUMAN 2.27 LHEAFSPVSYQHDLALLR_ FA12_HUMAN 2.14 699.4_251.2QGHNSVFLIK_381.6_520.4 HEMO_HUMAN 0.25 LLAPSDSPEWLSFDVTGVVR_ TGFB1_HUMAN−2.81 730.1_430.3 ELPQSIVYK_538.8_417.7 FBLN3_HUMAN −3.46VNHVTLSQPK_374.9_244.2 B2MG_HUMAN −6.61

TABLE 22 Lasso100 Middle Window Coef- Variable UniProt_ID ficientVFQFLEK_455.8_811.4 CO5_HUMAN 6.89 SEYGAALAWEK_612.8_788.4 CO6_HUMAN4.67 GEVTYTTSQVSK_650.3_750.4 EGLN_HUMAN 3.4 QVFAVQR_424.2_473.3ELNE_HUMAN 1.94 VELAPLPSWQPVGK_760.9_342.2 ICAM1_HUMAN 1.91LHEAFSPVSYQHDLALLR_ FA12_HUMAN 1.8 699.4_251.2 SLDFTELDVAAEK_719.4_316.2ANGT_HUMAN 1.67 YGIEEHGK_311.5_599.3 CXA1_HUMAN 1.53YGIEEHGK_311.5_341.2 CXA1_HUMAN 1.51 HYINLITR_515.3_301.1 NPY_HUMAN 1.47TLAFVR_353.7_492.3 FA7_HUMAN 1.46 GVTGYFTFNLYLK_508.3_260.2 PSG5_HUMAN1.28 FSLVSGWGQLLDR_493.3_403.2 FA7_HUMAN 0.84 DALSSVQESQVAQQAR_APOC3_HUMAN 0.41 573.0_502.3 VELAPLPSWQPVGK_760.9_400.3 ICAM1_HUMAN 0.3AVDIPGLEAATPYR_736.9_399.2 TENA_HUMAN −0.95 ELPQSIVYK_538.8_417.7FBLN3_HUMAN −1.54 DVLLLVHNLPQNLTGHIWYK_ PSG7_HUMAN −1.54 791.8_310.2VPLALFALNR_557.3_620.4 PEPD_HUMAN −1.91 LLAPSDSPEWLSFDVTGVVR_TGFB1_HUMAN −2.3 730.1_430.3 VNHVTLSQPK_374.9_244.2 B2MG_HUMAN −3.6EVFSKPISWEELLQ_852.9_376.2 FA40A_HUMAN −3.96

TABLE 23 Lasso Protein Middle Window Coef- Variable UniProt_ID ficientSEYGAALAWEK_612.8_788.4 CO6_HUMAN 5.84 VFQFLEK_455.8_811.4 CO5_HUMAN5.58 SLDFTELDVAAEK_719.4_316.2 ANGT_HUMAN 2.11 TLAFVR_353.7_492.3FA7_HUMAN 1.83 LHEAFSPVSYQHDLALLR_ FA12_HUMAN 1.62 699.4_251.2HYINLITR_515.3_301.1 NPY_HUMAN 1.39 VLEPTLK_400.3_458.3 VTDB_HUMAN 1.37YGIEEHGK_311.5_599.3 CXA1_HUMAN 1.17 VELAPLPSWQPVGK_ ICAM1_HUMAN 1.13760.9_342.2 QVFAVQR_424.2_473.3 ELNE_HUMAN 0.79 ANLINNIFELAGLGK_LCAP_HUMAN 0.23 793.9_299.2 DVLLLVHNLPQNLTGHIWYK_ PSG7_HUMAN −0.61791.8_310.2 VEHSDLSFSK_383.5_234.1 B2MG_HUMAN −0.69 AVDIPGLEAATPYR_TENA_HUMAN −0.85 736.9_399.2 VPLALFALNR_557.3_620.4 PEPD_HUMAN −1.45ELPQSIVYK_538.8_417.7 FBLN3_HUMAN −1.9 LLAPSDSPEWLSFDVTGVVR_ TGFB1_HUMAN−2.07 730.1_430.3 EVFSKPISWEELLQ_ FA40A_HUMAN −2.32 852.9_376.2

TABLE 24 Lasso All Middle Window Coef- Variable UniProt_ID ficientSEYGAALAWEK_612.8_788.4 CO6_HUMAN 2.48 VFQFLEK_455.8_811.4 CO5_HUMAN2.41 SLDFTELDVAAEK_719.4_316.2 ANGT_HUMAN 1.07 YGIEEHGK_311.5_599.3CXA1_HUMAN 0.64 VLEPTLK_400.3_458.3 VTDB_HUMAN 0.58 LHEAFSPVSYQHDLALLR_FA12_HUMAN 0.21 699.4_251.2 LLAPSDSPEWLSFDVTGVVR_ TGFB1_HUMAN −0.62730.1_430.3 VNHVTLSQPK_374.9_244.2 B2MG_HUMAN −1.28

TABLE 25 Lasso32 Middle-Late Window Coef- Variable UniProt_ID ficientSEYGAALAWEK_612.8_845.5 CO6_HUMAN 4.35 TLAFVR_353.7_492.3 FA7_HUMAN 2.42YGIEEHGK_311.5_599.3 CXA1_HUMAN 1.46 DFNQFSSGEK_386.8_333.2 FETA_HUMAN1.37 VFQFLEK_455.8_811.4 CO5_HUMAN 0.89 LIEIANHVDK_384.6_683.4ADA12_HUMAN 0.85 QINSYVK_426.2_496.3 CBG_HUMAN 0.56TYLHTYESEI_628.3_515.3 ENPP2_HUMAN 0.53 SLQAFVAVAAR_566.8_804.5IL23A_HUMAN 0.39 TEQAAVAR_423.2_615.4 FA12_HUMAN 0.26VLEPTLK_400.3_587.3 VTDB_HUMAN 0.24 AQPVQVAEGSEPDGFWEALGGK_ GELS_HUMAN−2.08 758.0_574.3 VPLALFALNR_557.3_620.4 PEPD_HUMAN −2.09AVYEAVLR_460.8_587.4 PEPD_HUMAN −3.37

TABLE 26 Lasso100 Middle-Late Window Variable UniProt_ID CoefficientVFQFLEK_455.8_811.4 CO5_HUMAN 3.82 SEYGAALAWEK_612.8_845.5 CO6_HUMAN2.94 YGIEEHGK_311.5_599.3 CXA1_HUMAN 2.39 DPTFIPAPIQAK_433.2_556.3ANGT_HUMAN 2.05 TLAFVR_353.7_492.3 FA7_HUMAN 1.9 NQSPVLEPVGR_598.3_866.5KS6A3_HUMAN 1.87 ALNHLPLEYNSALYSR_621.0_ CO6_HUMAN 1.4 538.3TQILEWAAER_608.8_761.4 EGLN_HUMAN 1.29 VVGGLVALR_442.3_784.5 FA12_HUMAN1.24 QINSYVK_426.2_496.3 CBG_HUMAN 1.14 YGIEEHGK_311.5_341.2 CXA1_HUMAN0.84 ALEQDLPVNIK_620.4_570.4 CNDP1_HUMAN 0.74 GTYLYNDCPGPGQDTDCR_697.0_TNR1A_HUMAN 0.51 666.3 SLCINASAIESILK_687.4_860.5 IL3_HUMAN 0.44DLHLSDVFLK_396.2_260.2 CO6_HUMAN 0.38 LIEIANHVDK_384.6_683.4 ADA12_HUMAN0.37 NIQSVNVK_451.3_674.4 GROA_HUMAN 0.3 FFQYDTWK_567.8_712.3 IGF2_HUMAN0.19 ANLINNIFELAGLGK_793.9_299.2 LCAP_HUMAN 0.19 TYLHTYESEI_628.3_515.3ENPP2_HUMAN 0.15 AALAAFNAQNNGSNFQLEEISR_ FETUA_HUMAN −0.09 789.1_746.4AQPVQVAEGSEPDGFWEALGGK_ GELS_HUMAN −0.52 758.0_574.3TSYQVYSK_488.2_787.4 C163A_HUMAN −0.62 AVDIPGLEAATPYR_736.9_399.2TENA_HUMAN −1.29 TAHISGLPPSTDFIVYLSGLAPSIR_ TENA_HUMAN −1.53 871.5_472.3AEIEYLEK_497.8_552.3 LYAM1_HUMAN −1.73 LLAPSDSPEWLSFDVTGVVR_730.1_TGFB1_HUMAN −1.95 430.3 VPLALFALNR_557.3_620.4 PEPD_HUMAN −2.9AVYEAVLR_460.8_587.4 PEPD_HUMAN −3.04 ELPQSIVYK_538.8_417.7 FBLN3_HUMAN−3.49 EVFSKPISWEELLQ_852.9_376.2 FA40A_HUMAN −3.71

TABLE 27 Lasso Protein Middle-LateWindow Variable UniProt_ID CoefficientVFQFLEK_455.8_811.4 CO5_HUMAN 4.25 ALNHLPLEYNSALYSR_621.0_ CO6_HUMAN3.06 696.4 YGIEEHGK_311.5_599.3 CXA1_HUMAN 2.36 SEPRPGVLLR_375.2_654.4FA7_HUMAN 2.11 TQILEWAAER_608.8_761.4 EGLN_HUMAN 1.81NQSPVLEPVGR_598.3_866.5 KS6A3_HUMAN 1.79 TEQAAVAR_423.2_615.4 FA12_HUMAN1.72 QINSYVK_426.2_496.3 CBG_HUMAN 0.98 ALEQDLPVNIK_620.4_570.4CNDP1_HUMAN 0.98 NCSFSIIYPVVIK_770.4_555.4 CRHBP_HUMAN 0.76LIEIANHVDK_384.6_683.4 ADA12_HUMAN 0.63 SLCINASAIESILK_687.4_860.5IL3_HUMAN 0.59 ANLINNIFELAGLGK_793.9_299.2 LCAP_HUMAN 0.55GTYLYNDCPGPGQDTDCR_697.0_ TNR1A_HUMAN 0.55 666.3 TYLHTYESEI_628.3_515.3ENPP2_HUMAN 0.46 NIQSVNVK_451.3_674.4 GROA_HUMAN 0.22LTTVDIVTLR_565.8_815.5 IL2RB_HUMAN 0.11 FFQYDTWK_567.8_712.3 IGF2_HUMAN0.01 TSYQVYSK_488.2_787.4 C163A_HUMAN −0.76 AQPVQVAEGSEPDGFWEALGGK_GELS_HUMAN −1.31 758.0_574.3 AEIEYLEK_497.8_552.3 LYAM1_HUMAN −1.59LLAPSDSPEWLSFDVTGVVR_ TGFB1_HUMAN −1.73 730.1_430.3AVDIPGLEAATPYR_736.9_399.2 TENA_HUMAN −2.02 EVFSKPISWEELLQ_852.9_376.2FA40A_HUMAN −3 TGVAVNKPAEFTVDAK_549.6_ FLNA_HUMAN −3.15 258.1ELPQSIVYK_538.8_417.7 FBLN3_HUMAN −3.49 VNHVTLSQPK_374.9_244.2B2MG_HUMAN −3.82 VPLALFALNR_557.3_620.4 PEPD_HUMAN −4.94

TABLE 28 Lasso All Middle-LateWindow Variable UniProt_ID CoefficientALNHLPLEYNSALYSR_621.0_ CO6_HUMAN 2.38 538.3 TLAFVR_353.7_492.3FA7_HUMAN 0.96 YGIEEHGK_311.5_599.3 CXA1_HUMAN 0.34DPTFIPAPIQAK_433.2_461.2 ANGT_HUMAN 0.33 DFNQFSSGEK_386.8_333.2FETA_HUMAN 0.13 QINSYVK_426.2_496.3 CBG_HUMAN 0.03TYLHTYESEI_628.3_515.3 ENPP2_HUMAN 0 AQPVQVAEGSEPDGFWEALGGK_ GELS_HUMAN−0.02 758.0_574.3 AEIEYLEK_497.8_552.3 LYAM1_HUMAN −0.05VNHVTLSQPK_374.9_244.2 B2MG_HUMAN −0.12 LLAPSDSPEWLSFDVTGVVR_730._TGFB1_HUMAN −0.17 1430.3 EVFSKPISWEELLQ_852.9_376.2 FA40A_HUMAN −0.31AVDIPGLEAATPYR_736.9_399.2 TENA_HUMAN −0.35 VPLALFALNR_557.3_620.4PEPD_HUMAN −0.43 AVYEAVLR_460.8_587.4 PEPD_HUMAN −2.33

TABLE 29 Lasso 32 LateWindow Variable UniProt_ID CoefficientQINSYVK_426.2_610.3 CBG_HUMAN 3.24 ILDGGNK_358.7_603.3 CXCL5_HUMAN 2.65VFQYIDLHQDEFVQTLK_708.4_ CNDP1_HUMAN 2.55 375.2 SGVDLADSNQK_567.3_662.3VGFR3_HUMAN 2.12 YSHYNER_323.5_418.2 HABP2_HUMAN 1.63DEIPHNDIALLK_459.9_510.8 HABP2_HUMAN 1.22 SGVDLADSNQK_567.3_591.3VGFR3_HUMAN 0.96 FGFGGSTDSGPIR_649.3_745.4 ADA12_HUMAN 0.86GTYLYNDCPGPGQDTDCR_697.0_ TNR1A_HUMAN 0.45 666.3 TSYQVYSK_488.2_787.4C163A_HUMAN −1.73 TGVAVNKPAEFTVDAK_549.6_ FLNA_HUMAN −2.56 258.1SPEAEDPLGVER_649.8_314.1 Z512B_HUMAN −3.04 VPLALFALNR_557.3_620.4PEPD_HUMAN −3.33 YYGYTGAFR_549.3_450.3 TRFL_HUMAN −4.24AVYEAVLR_460.8_587.4 PEPD_HUMAN −5.83 AEIEYLEK_497.8_552.3 LYAM1_HUMAN−6.52 AALAAFNAQNNGSNFQLEEISR_ FETUA_HUMAN −6.55 789.1_746.4

TABLE 30 Lasso 100 Late Window Variable UniProt_ID CoefficientSGVDLADSNQK_567.3_662.3 VGFR3_HUMAN 4.13 ILDGGNK_358.7_603.3 CXCL5_HUMAN3.57 QINSYVK_426.2_610.3 CBG_HUMAN 3.41 DEIPHNDIALLK_459.9_510.8HABP2_HUMAN 1.64 VFQYIDLHQDEFVQTLK_708.4_ CNDP1_HUMAN 1.57 375.2FGFGGSTDSGPIR_649.3_745.4 ADA12_HUMAN 1.45 LTTVDIVTLR_565.8_815.5IL2RB_HUMAN 0.71 YSHYNER_323.5_418.2 HABP2_HUMAN 0.68FFQYDTWK_567.8_712.3 IGF2_HUMAN 0.42 IEVNESGTVASSSTAVIVSAR_ PAI1_HUMAN0.36 693.0_545.3 GTYLYNDCPGPGQDTDCR_697.0_ TNR1A_HUMAN 0.21 666.3LIEIANHVDK_384.6_683.4 ADA12_HUMAN 0.1 VGVISFAQK_474.8_580.3 TFR2_HUMAN0.08 TSYQVYSK_488.2_787.4 C163A_HUMAN −0.36 ALNFGGIGVVVGHELTHAFDDQGR_ECE1_HUMAN −0.65 837.1_360.2 AYSDLSR_406.2_375.2 SAMP_HUMAN −1.23TGVAVNKPAEFTVDAK_549.6_ FLNA_HUMAN −1.63 258.1 SPEAEDPLGVER_649.8_314.1Z512B_HUMAN −2.29 YYGYTGAFR_549.3_450.3 TRFL_HUMAN −2.58VPLALFALNR_557.3_620.4 PEPD_HUMAN −2.73 YISPDQLADLYK_713.4_277.2ENOA_HUMAN −2.87 AVDIPGLEAATPYR_736.9_286.1 TENA_HUMAN −3.9AEIEYLEK_497.8_552.3 LYAM1_HUMAN −5.29 AVYEAVLR_460.8_587.4 PEPD_HUMAN−5.51 AALAAFNACINNGSNFQLEEISR_ FETUA_HUMAN −6.49 789.1_746.4

TABLE 31 Lasso Protein Late Window Variable UniProt_ID CoefficientSGVDLADSNQK_567.3_662.3 VGFR3_HUMAN 3.33 ILDGGNK_358.7_603.3 CXCL5_HUMAN3.25 QINSYVK_426.2_496.3 CBG_HUMAN 2.41 YSHYNER_323.5_418.2 HABP2_HUMAN1.82 ALEQDLPVNIK_620.4_798.5 CNDP1_HUMAN 1.32 LIEIANHVDK_384.6_683.4ADA12_HUMAN 1.27 GTYLYNDCPGPGQDTDCR_ TNR1A_HUMAN 0.26 697.0_666.3IEVNESGTVASSSTAVIVSAR_ PAI1_HUMAN 0.18 693.0_545.3LTTVDIVTLR_565.8_815.5 IL2RB_HUMAN 0.18 TSYQVYSK_488.2_787.4 C163A_HUMAN−0.11 TGVAVNKPAEFTVDAK_549.6_ FLNA_HUMAN −0.89 258.1 AYSDLSR_406.2_375.2SAMP_HUMAN −1.47 SPEAEDPLGVER_649.8_314.1 Z512B_HUMAN −1.79YYGYTGAFR_549.3_450.3 TRFL_HUMAN −2.22 YISPDQLADLYK_713.4_277.2ENOA_HUMAN −2.41 AVDIPGLEAATPYR_736.9_286.1 TENA_HUMAN −2.94AEIEYLEK_497.8_552.3 LYAM1_HUMAN −5.18 AALAAFNAQNNGSNFQLEEISR_FETUA_HUMAN −5.71 789.1_746.4 AVYEAVLR_460.8_587.4 PEPD_HUMAN −7.33

TABLE 32 Lasso All Late Window Variable UniProt_ID CoefficientQINSYVK_426.2_496.3 CBG_HUMAN 0.5 DEIPHNDIALLK_459.9_510.8 HABP2_HUMAN0.15 ALEQDLPVNIK_620.4_570.4 CNDP1_HUMAN 0.11 ILDGGNK_358.7_603.3CXCL5_HUMAN 0.08 LIEIANHVDK_384.6_683.4 ADA12_HUMAN 0.06YYGYTGAFR_549.3_450.3 TRFL_HUMAN −0.39 AALAAFNACINNGSNFQLEEISR_FETUA_HUMAN −1.57 789.1_746.4 AEIEYLEK_497.8_552.3 LYAM1_HUMAN −2.46AVYEAVLR_460.8_587.4 PEPD_HUMAN −2.92

TABLE 33 Random Forest 32 Early Window Variable Protein MeanDecreaseGiniELIEELVNITQNQK_557.6_ IL13_HUMAN  3.224369171 517.3 AHYDLR_387.7_288.2FETUA_HUMAN  1.869007658 FSVVYAK_407.2_381.2 FETUA_HUMAN  1.770198171ITLPDFTGDLR_624.3_ LBP_HUMAN  1.710936472 288.2 ITGFLKPGK_320.9_301.2LBP_HUMAN  1.623922439 ITGFLKPGK_320.9_429.3 LBP_HUMAN  1.408035272ELIEELVNITQNQK_557.6_ IL13_HUMAN  1.345412168 618.3 VFQFLEK_455.8_811.4CO5_HUMAN  1.311332013 VQTAHFK_277.5_431.2 CO8A_HUMAN  1.308902373FLNWIK_410.7_560.3 HABP2_HUMAN  1.308093745 DAGLSWGSAR_510.3_390.2NEUR4_HUMAN  1.297033607 TLLPVSKPEIR_418.3_ CO5_HUMAN  1.291280928 288.2LIQDAVTGLTVNGQITGDK_ ITIH3_HUMAN 1.28622301 972.0_798.4QALEEFQK_496.8_680.3 CO8B_HUMAN  1.191731825 FSVVYAK_407.2_579.4FETUA_HUMAN  1.078909138 ITLPDFTGDLR_624.3_ LBP_HUMAN  1.072613747 920.5AHYDLR_387.7_566.3 FETUA_HUMAN  1.029562263 ALNHLPLEYNSALYSR_ CO6_HUMAN1.00992071 621.0_538.3 DVLLLVHNLPQNLPGYFWYK_ PSG9_HUMAN  1.007095529810.4_967.5 SFRPFVPR_335.9_635.3 LBP_HUMAN  0.970312536SDLEVAHYK_531.3_617.3 CO8B_HUMAN  0.967904893 VQEAHLTEDQIFYFPK_CO8G_HUMAN  0.960398254 655.7_701.4 VFQFLEK_455.8_276.2 CO5_HUMAN 0.931652095 SLLQPNK_400.2_599.4 CO8A_HUMAN  0.926470249SFRPFVPR_335.9_272.2 LBP_HUMAN  0.911599611 FLNWIK_410.7_561.3HABP2_HUMAN  0.852022868 LSSPAVITDK_515.8_743.4 PLMN_HUMAN  0.825455824DVLLLVHNLPQNLPGYFWYK_ PSG9_HUMAN  0.756797142 810.4_594.3ALVLELAK_428.8_672.4 INHBE_HUMAN  0.748802555 DISEVVTPR_508.3_787.4CFAB_HUMAN  0.733731518

TABLE 34 Random Forest 100 Early Window Variable ProteinMeanDecreaseGini ELIEELVNITQNQK_557.6_ IL13_HUMAN   1.709778508 517.3LPNNVLQEK_527.8_844.5 AFAM_HUMAN   0.961692716 AHYDLR_387.7_288.2FETUA_HUMAN   0.901586746 ITLPDFTGDLR_624.3_ LBP_HUMAN   0.879119498288.2 IEGNLIFDPNNYLPK_874.0_ APOB_HUMAN   0.842483095 414.2ITGFLKPGK_320.9_301.2 LBP_HUMAN   0.806905233 FSVVYAK_407.2_381.2FETUA_HUMAN   0.790429706 ITGFLKPGK_320.9_429.3 LBP_HUMAN   0.710312386VFQFLEK_455.8_811.4 CO5_HUMAN   0.709531553 LIQDAVTGLTVNGQITGDK_ITIH3_HUMAN   0.624325189 972.0_798.4 DADPDTFFAK_563.8_825.4 AFAM_HUMAN  0.618684313 FLNWIK_410.7_560.3 HABP2_HUMAN   0.617501242TASDFITK_441.7_781.4 GELS_HUMAN   0.609275999 DAGLSWGSAR_510.3_390.2NEUR4_HUMAN   0.588718595 VQTAHFK_277.5_431.2 CO8A_HUMAN  0.58669845TLLPVSKPEIR_418.3_ COS_HUMAN 0.5670608 288.2 ELIEELVNITQNQK_557.6_IL13_HUMAN   0.555624783 618.3 TYLHTYESEI_628.3_908.4 ENPP2_HUMAN  0.537678415 HFQNLGK_422.2_527.2 AFAM_HUMAN   0.535543137TASDFITK_441.7_710.4 GELS_HUMAN   0.532743323 ITLPDFTGDLR_624.3_LBP_HUMAN  0.51667902 920.5 QALEEFQK_496.8_680.3 CO8B_HUMAN  0.511314017 AVLHIGEK_289.5_348.7 THBG_HUMAN   0.510284122FSVVYAK_407.2_579.4 FETUA_HUMAN   0.503907813 LPNNVLQEK_527.8_730.4AFAM_HUMAN   0.501281631 AHYDLR_387.7_566.3 FETUA_HUMAN   0.474166711IAPQLSTEELVSLGEK_ AFAM_HUMAN   0.459595701 857.5_333.2WWGGQPLWITATK_772.4_ ENPP2_HUMAN  0.44680777 929.5TYLHTYESEI_628.3_515.3 ENPP2_HUMAN   0.434157773 DALSSVQESQVAQQAR_APOC3_HUMAN   0.432484862 573.0_502.3

TABLE 35 Random Forest Protein Early Window Variable ProteinMeanDecreaseGini ELIEELVNITQNQK_557.6_ IL13_HUMAN  2.881452809 517.3LPNNVLQEK_527.8_844.5 AFAM_HUMAN  1.833987752 ITLPDFTGDLR_624.3_288.2LBP_HUMAN  1.608843881 IEGNLIFDPNNYLPK_874.0_ APOB_HUMAN  1.594658208414.2 VFQFLEK_455.8_811.4 CO5_HUMAN  1.290134412 LIQDAVTGLTVNGQITGDK_ITIH3_HUMAN  1.167981736 972.0_798.4 TASDFITK_441.7_781.4 GELS_HUMAN 1.152847453 DAGLSWGSAR_510.3_390.2 NEUR4_HUMAN  1.146752656FSVVYAK_407.2_579.4 FETUA_HUMAN  1.060168583 AVLHIGEK_289.5_348.7THBG_HUMAN  1.033625773 FLNWIK_410.7_560.3 HABP2_HUMAN  1.022356789QALEEFQK_496.8_680.3 CO8B_HUMAN  0.990074129 DVLLLVHNLPQNLPGYFWYK_PSG9_HUMAN  0.929633865 810.4_967.5 WWGGQPLWITATK_772.4_ ENPP2_HUMAN 0.905895642 929.5 VQEAHLTEDQIFYFPK_ CO8G_HUMAN  0.883887371 655.7_701.4NNQLVAGYLQGPNVNLEEK_ IL1RA_HUMAN  0.806472085 700.7_999.5SLLQPNK_400.2_599.4 CO8A_HUMAN  0.783623222 DALSSVQESQVAQQAR_APOC3_HUMAN  0.774365756 573.0_672.4 NIQSVNVK_451.3_674.4 GROA_HUMAN 0.767963386 HPWIVHWDQLPQYQLNR_ KS6A3_HUMAN  0.759960139 744.0_1047.0TTSDGGYSFK_531.7_860.4 INHA_HUMAN  0.732813448 ALNHLPLEYNSALYSR_CO6_HUMAN  0.718779092 621.0_538.3 LSSPAVITDK_515.8_743.4 PLMN_HUMAN 0.699547739 TGVAVNKPAEFTVDAK_ FLNA_HUMAN  0.693159192 549.6_258.1TLNAYDHR_330.5_312.2 PAR3_HUMAN  0.647300964 DISEVVTPR_508.3_787.4CFAB_HUMAN  0.609165621 LIENGYFHPVK_439.6_627.4 F13B_HUMAN 0.60043345SGVDLADSNQK_567.3_662.3 VGFR3_HUMAN  0.596079858 ALQDQLVLVAAK_634.9_ANGT_HUMAN  0.579034994 289.2 ALVLELAK_428.8_672.4 INHBE_HUMAN 0.573458483

TABLE 36 Random Forest All Early Window Variable ProteinMeanDecreaseGini ELIEELVNITQNQK_557.6_ IL13_HUMAN  0.730972421 517.3ITLPDFTGDLR_624.3_288.2 LBP_HUMAN  0.409808774 AHYDLR_387.7_288.2FETUA_HUMAN  0.409298983 FSVVYAK_407.2_381.2 FETUA_HUMAN  0.367730833ITGFLKPGK_320.9_301.2 LBP_HUMAN  0.350485117 VFQFLEK_455.8_811.4CO5_HUMAN  0.339289475 ELIEELVNITQNQK_557.6_ IL13_HUMAN  0.334303166618.3 LPNNVLQEK_527.8_844.5 AFAM_HUMAN  0.329800706 IEGNLIFDPNNYLPK_APOB_HUMAN  0.325596677 874.0_414.2 ITGFLKPGK_320.9_429.3 LBP_HUMAN0.31473104 FLNWIK_410.7_560.3 HABP2_HUMAN  0.299810081LIQDAVTGLTVNGQITGDK_ ITIH3_HUMAN  0.295613448 972.0_798.4ITLPDFTGDLR_624.3_920.5 LBP_HUMAN  0.292212699 DAGLSWGSAR_510.3_390.2NEUR4_HUMAN  0.285812225 TLLPVSKPEIR_418.3_288.2 CO5_HUMAN  0.280857718FSVVYAK_407.2_579.4 FETUA_HUMAN  0.278531322 DADPDTFFAK_563.8_825.4AFAM_HUMAN  0.258938798 AHYDLR_387.7_566.3 FETUA_HUMAN  0.256160046QALEEFQK_496.8_680.3 CO8B_HUMAN  0.245543641 HTLNQIDEVK_598.8_951.5FETUA_HUMAN  0.239528081 TASDFITK_441.7_781.4 GELS_HUMAN  0.227485958VFQFLEK_455.8_276.2 CO5_HUMAN  0.226172392 DVLLLVHNLPQNLPGYFWYK_PSG9_HUMAN  0.218613384 810.4_967.5 VQTAHFK_277.5_431.2 CO8A_HUMAN 0.217171548 SFRPFVPR_335.9_635.3 LBP_HUMAN  0.214798112HFQNLGK_422.2_527.2 AFAM_HUMAN  0.211756476 SVSLPSLDPASAK_636.4_APOB_HUMAN  0.211319422 473.3 FGFGGSTDSGPIR_649.3_ ADA12_HUMAN 0.206574494 745.4 HFQNLGK_422.2_285.1 AFAM_HUMAN  0.204024196AVLHIGEK_289.5_348.7 THBG_HUMAN  0.201102917

TABLE 37 Random Forest SummedGini Early Window Transition ProteinSumBestGini ELIEELVNITQNQK_557.6_517.3 IL13_HUMAN 242.5373659VFQFLEK_455.8_811.4 CO5_HUMAN 115.1113943 FLNWIK_410.7_560.3 HABP2_HUMAN107.4572447 ITLPDFTGDLR_624.3_288.2 LBP_HUMAN 104.0742727LIQDAVTGLTVNGQITGDK_972.0_798.4 ITIH3_HUMAN 103.3238077DAGLSWGSAR_510.3_390.2 NEUR4_HUMAN 70.4151533 AHYDLR_387.7_288.2FETUA_HUMAN 140.2670822 FSVVYAK_407.2_381.2 FETUA_HUMAN 121.3664352LPNNVLQEK_527.8_844.5 AFAM_HUMAN 115.5211679 ITGFLKPGK_320.9_429.3LBP_HUMAN 114.9512704 ITGFLKPGK_320.9_301.2 LBP_HUMAN 112.916627IEGNLIFDPNNYLPK_874.0_414.2 APOB_HUMAN 52.21169288 VQTAHFK_277.5_431.2CO8A_HUMAN 144.5237215 TLLPVSKPEIR_418.3_288.2 CO5_HUMAN 96.16982897QALEEFQK_496.8_680.3 CO8B_HUMAN 85.35050759 FSVVYAK_407.2_579.4FETUA_HUMAN 73.23969945 ELIEELVNITQNQK_557.6_618.3 IL13_HUMAN61.61450671 TASDFITK_441.7_781.4 GELS_HUMAN 61.32155633DVLLLVHNLPQNLPGYFWYK_810.4_967.5 PSG9_HUMAN 99.68404123AVLHIGEK_289.5_348.7 THBG_HUMAN 69.96748485 ITLPDFTGDLR_624.3_920.5LBP_HUMAN 56.66810872 WWGGQPLWITATK_772.4_929.5 ENPP2_HUMAN 56.54173176VQEAHLTEDQIFYFPK_655.7_701.4 CO8G_HUMAN 47.92505575DADPDTFFAK_563.8_825.4 AFAM_HUMAN 40.34147696DALSSVQESQVAQQAR_573.0_502.3 APOC3_HUMAN 145.0311483FGFGGSTDSGPIR_649.3_745.4 ADA12_HUMAN 109.4072996 FLPCENK_454.2_550.2IL10_HUMAN 105.7756691 VQTAHFK_277.5_502.3 CO8A_HUMAN 101.5877845VFQFLEK_455.8_276.2 CO5_HUMAN 95.71159157 TYLHTYESEI_628.3_908.4ENPP2_HUMAN 94.92157517 ALNHLPLEYNSALYSR_621.0_538.3 CO6_HUMAN90.67568777 NKPGVYTDVAYYLAWIR_677.0_545.3 FA12_HUMAN 90.35890105LEEHYELR_363.5_580.3 PAI2_HUMAN 88.44833508HPWIVHWDQLPQYQLNR_744.0_1047.0 KS6A3_HUMAN 88.37680942HTLNQIDEVK_598.8_951.5 FETUA_HUMAN 87.63064143 LPNNVLQEK_527.8_730.4AFAM_HUMAN 86.64484642 ALDLSLK_380.2_575.3 ITIH3_HUMAN 83.51201287YGIEEHGK_311.5_599.3 CXA1_HUMAN 82.47620831 LSSPAVITDK_515.8_830.5PLMN_HUMAN 81.5433587 LEEHYELR_363.5_288.2 PAI2_HUMAN 79.01571985NVIQISNDLENLR_509.9_402.3 LEP_HUMAN 78.86670236 SGFSFGFK_438.7_732.4CO8B_HUMAN 78.71961929 SDLEVAHYK_531.3_617.3 CO8B_HUMAN 78.24005567NADYSYSVWK_616.8_333.2 CO5_HUMAN 76.07974354 AHYDLR_387.7_566.3FETUA_HUMAN 74.68253347 GAVHVVVAETDYQSFAVLYLER_822.8_580.3 CO8G_HUMAN73.75860248 LIENGYFHPVK_439.6_627.4 F13B_HUMAN 73.74965194ALDLSLK_380.2_185.1 ITIH3_HUMAN 72.760739 WWGGQPLWITATK_772.4_373.2ENPP2_HUMAN 72.51936706 FGFGGSTDSGPIR_649.3_946.5 ADA12_HUMAN72.49183198 GLQYAAQEGLLALQSELLR_1037.1_929.5 LBP_HUMAN 67.17588648HFQNLGK_422.2_527.2 AFAM_HUMAN 66.11702719 YSHYNER_323.5_581.3HABP2_HUMAN 65.56238612 ISQGEADINIAFYQR_575.6_684.4 MMP8_HUMAN65.50301246 TGVAVNKPAEFTVDAK_549.6_258.1 FLNA_HUMAN 64.85259525NIQSVNVK_451.3_674.4 GROA_HUMAN 64.53010225 DALSSVQESQVAQQAR_573.0_672.4APOC3_HUMAN 64.12149927 SLLQPNK_400.2_599.4 CO8A_HUMAN 62.68167847SFRPFVPR_335.9_635.3 LBP_HUMAN 61.90157662NNQLVAGYLQGPNVNLEEK_700.7_999.5 IL1RA_HUMAN 61.54435815LYYGDDEK_501.7_563.2 CO8A_HUMAN 60.16700473 SWNEPLYHLVTEVR_581.6_716.4PRL_HUMAN 59.78209065 SGVDLADSNQK_567.3_662.3 VGFR3_HUMAN 58.93982896GTYLYNDCPGPGQDTDCR_697.0_335.2 TNR1A_HUMAN 58.72963941HATLSLSIPR_365.6_472.3 VGFR3_HUMAN 57.98669834 FIVGFTR_420.2_261.2CCL20_HUMAN 57.23165578 QNYHQDSEAAINR_515.9_544.3 FRIH_HUMAN 57.21116697DVLLLVHNLPQNLPGYFWYK_810.4_594.3 PSG9_HUMAN 56.84150484FLNWIK_410.7_561.3 HABP2_HUMAN 56.37258274 SLQAFVAVAAR_566.8_487.3IL23A_HUMAN 56.09012981 HFQNLGK_422.2_285.1 AFAM_HUMAN 56.04480022GPGEDFR_389.2_322.2 PTGDS_HUMAN 55.7583763 NKPGVYTDVAYYLAWIR_677.0_821.5FA12_HUMAN 55.53857645 LIQDAVTGLTVNGQITGDK_972.0_640.4 ITIH3_HUMAN55.52577583 YYGYTGAFR_549.3_450.3 TRFL_HUMAN 54.27147366TLNAYDHR_330.5_312.2 PAR3_HUMAN 54.19190934 IQTHSTTYR_369.5_627.3F13B_HUMAN 54.18950583 TASDFITK_441.7_710.4 GELS_HUMAN 54.1056456ALNHLPLEYNSALYSR_621.0_696.4 CO6_HUMAN 53.8997252 DADPDTFFAK_563.8_302.1AFAM_HUMAN 53.85914848 SVSLPSLDPASAK_636.4_473.3 APOB_HUMAN 53.41996191TTSDGGYSFK_531.7_860.4 INHA_HUMAN 52.24655536 AFTECCVVASQLR_770.9_574.3CO5_HUMAN 51.67853429 ELPQSIVYK_538.8_409.2 FBLN3_HUMAN 51.35853002TYLHTYESEI_628.3_515.3 ENPP2_HUMAN 51.23842124 FQLSETNR_497.8_605.3PSG2_HUMAN 51.01576848 GSLVQASEANLQAAQDFVR_668.7_806.4 ITIH1_HUMAN50.81923338 FSLVSGWGQLLDR_493.3_403.2 FA7_HUMAN 50.54425114ECEELEEK_533.2_405.2 IL15_HUMAN 50.41977421 NADYSYSVWK_616.8_769.4CO5_HUMAN 50.36434595 SLLQPNK_400.2_358.2 CO8A_HUMAN 49.75593162LIEIANHVDK_384.6_683.4 ADA12_HUMAN 49.43389721 DISEVVTPR_508.3_787.4CFAB_HUMAN 49.00234897 AEVIWTSSDHQVLSGK_586.3_300.2 PD1L1_HUMAN48.79028835 SGVDLADSNQK_567.3_591.3 VGFR3_HUMAN 48.70665587SILFLGK_389.2_201.1 THBG_HUMAN 48.5997957 AVLHIGEK_289.5_292.2THBG_HUMAN 48.4605866 QLYGDTGVLGR_589.8_501.3 CO8G_HUMAN 48.11414904FSLVSGWGQLLDR_493.3_516.3 FA7_HUMAN 47.59635333DSPVLIDFFEDTER_841.9_399.2 HRG_HUMAN 46.83840473 INPASLDK_429.2_630.4C163A_HUMAN 46.78947931 GAVHVVVAETDYQSFAVLYLER_822.8_863.5 CO8G_HUMAN46.66185339 FLQEQGHR_338.8_497.3 CO8G_HUMAN 46.64415952LNIGYIEDLK_589.3_837.4 PAI2_HUMAN 46.5879123 LSSPAVITDK_515.8_743.4PLMN_HUMAN 46.2857838 GLQYAAQEGLLALQSELLR_1037.1_858.5 LBP_HUMAN45.7427767 SDGAKPGPR_442.7_213.6 COLI_HUMAN 45.27828366GYQELLEK_490.3_502.3 FETA_HUMAN 43.52928868 GGEGTGYFVDFSVR_745.9_869.5HRG_HUMAN 43.24514327 ADLFYDVEALDLESPK_913.0_447.2 HRG_HUMAN 42.56268679ADLFYDVEALDLESPK_913.0_331.2 HRG_HUMAN 42.48967422EAQLPVIENK_570.8_699.4 PLMN_HUMAN 42.21213429 SILFLGK_389.2_577.4THBG_HUMAN 42.03379581 HTLNQIDEVK_598.8_958.5 FETUA_HUMAN 41.98377176AQPVQVAEGSEPDGFWEALGGK_758.0_574.3 GELS_HUMAN 41.89547273FLPCENK_454.2_390.2 IL10_HUMAN 41.66612478 LIEIANHVDK_384.6_498.3ADA12_HUMAN 41.50878046 DEIPHNDIALLK_459.9_510.8 HABP2_HUMAN 41.27830935SLQAFVAVAAR_566.8_804.5 IL23A_HUMAN 41.00430596 YISPDQLADLYK_713.4_277.2ENOA_HUMAN 40.90053801 SLPVSDSVLSGFEQR_810.9_836.4 CO8G_HUMAN40.62020941 DGSPDVTTADIGANTPDATK_973.5_531.3 PGRP2_HUMAN 40.33913091NTGVISVVTTGLDR_716.4_662.4 CADH1_HUMAN 40.05291612 ALVLELAK_428.8_672.4INHBE_HUMAN 40.01646465 YEFLNGR_449.7_293.1 PLMN_HUMAN 39.83344278WGAAPYR_410.7_577.3 PGRP2_HUMAN 39.52766213 TFLTVYWTPER_706.9_401.2ICAM1_HUMAN 39.13662034 SEYGAALAWEK_612.8_845.5 CO6_HUMAN 38.77511119VGVISFAQK_474.8_693.4 TFR2_HUMAN 38.5823457 IIEVEEEQEDPYLNDR_996.0_777.4FBLN1_HUMAN 38.30913304 TGYYFDGISR_589.8_694.4 FBLN1_HUMAN 38.30617106LQGTLPVEAR_542.3_571.3 CO5_HUMAN 37.93064544 DSPVLIDFFEDTER_841.9_512.3HRG_HUMAN 37.4447737 AALAAFNAQNNGSNFQLEEISR_789.1_746.4 FETUA_HUMAN37.02483715 DGSPDVTTADIGANTPDATK_973.5_844.4 PGRP2_HUMAN 36.59864788ILILPSVTR_506.3_785.5 PSGx_HUMAN 36.43814815 SVSLPSLDPASAK_636.4_885.5APOB_HUMAN 36.27689491 TLAFVR_353.7_492.3 FA7_HUMAN 36.18771771VAPGVANPGTPLA_582.3_555.3 A6NIT4_HUMAN 35.70677357HELTDEELQSLFTNFANVVDK_817.1_906.5 AFAM_HUMAN 35.14441609AGLLRPDYALLGHR_518.0_369.2 PGRP2_HUMAN 35.13047098GDTYPAELYITGSILR_885.0_1332.8 F13B_HUMAN 34.97832404LFIPQITR_494.3_727.4 PSG9_HUMAN 34.76811249 GYQELLEK_490.3_631.4FETA_HUMAN 34.76117605 VSEADSSNADWVTK_754.9_533.3 CFAB_HUMAN 34.49787512LNIGYIEDLK_589.3_950.5 PAI2_HUMAN 34.48448691 SFRPFVPR_335.9_272.2LBP_HUMAN 34.27529415 ILDGGNK_358.7_490.2 CXCL5_HUMAN 34.2331388EANQSTLENFLER_775.9_678.4 IL4_HUMAN 34.14295797 DFNQFSSGEK_386.8_189.1FETA_HUMAN 34.05459951 IEEIAAK_387.2_660.4 CO5_HUMAN 33.93778148TEFLSNYLTNVDDITLVPGTLGR_846.8_600.3 ENPP2_HUMAN 33.87864446LPATEKPVLLSK_432.6_347.2 HYOU1_HUMAN 33.69005522 FLQEQGHR_338.8_369.2CO8G_HUMAN 33.61179024 APLTKPLK_289.9_357.2 CRP_HUMAN 33.59900279YSHYNER_323.5_418.2 HABP2_HUMAN 33.50888447 TSYQVYSK_488.2_787.4C163A_HUMAN 33.11650018 IALGGLLFPASNLR_481.3_657.4 SHBG_HUMAN33.02974341 TGISPLALIK_506.8_741.5 APOB_HUMAN 32.64471573LYYGDDEK_501.7_726.3 CO8A_HUMAN 32.60782458IVLSLDVPIGLLQILLEQAR_735.1_503.3 UCN2_HUMAN 32.37907686EAQLPVIENK_570.8_329.2 PLMN_HUMAN 32.34049256 TGYYFDGISR_589.8_857.4FBLN1_HUMAN 32.14526507 VGVISFAQK_474.8_580.3 TFR2_HUMAN 32.11753213FQSVFTVTR_542.8_623.4 C1QC_HUMAN 32.11360444 TSDQIHFFFAK_447.6_659.4ANT3_HUMAN 31.95867038 IAPQLSTEELVSLGEK_857.5_333.2 AFAM_HUMAN31.81531364 EVFSKPISWEELLQ_852.9_260.2 FA40A_HUMAN 31.36698726DEIPHNDIALLK_459.9_260.2 HABP2_HUMAN 31.1839869NYFTSVAHPNLFIATK_608.3_319.2 ILIA_HUMAN 31.09867061ITENDIQIALDDAK_779.9_632.3 APOB_HUMAN 30.77026845 DTYVSSFPR_357.8_272.2TCEA1_HUMAN 30.67784731 TDAPDLPEENQAR_728.3_843.4 CO5_HUMAN 30.66251941LFYADHPFIFLVR_546.6_647.4 SERPH_HUMAN 30.65831566 TEQAAVAR_423.2_487.3FA12_HUMAN 30.44356842 AVGYLITGYQR_620.8_737.4 PZP_HUMAN 30.36425528HSHESQDLR_370.2_288.2 HRG_HUMAN 30.34684703 IALGGLLFPASNLR_481.3_412.3SHBG_HUMAN 30.34101643 IAQYYYTFK_598.8_884.4 F13B_HUMAN 30.23453833SLPVSDSVLSGFEQR_810.9_723.3 CO8G_HUMAN 30.11396489IIGGSDADIK_494.8_762.4 C1S_HUMAN 30.06572687 QTLSWTVTPK_580.8_545.3PZP_HUMAN 30.04139865 HYFIAAVER_553.3_658.4 FA8_HUMAN 29.80239884QVCADPSEEWVQK_788.4_374.2 CCL3_HUMAN 29.61435573 DLHLSDVFLK_396.2_366.2CO6_HUMAN 29.60077507 NIQSVNVK_451.3_546.3 GROA_HUMAN 29.47619619QTLSWTVTPK_580.8_818.4 PZP_HUMAN 29.40047934 HSHESQDLR_370.2_403.2HRG_HUMAN 29.32242262 LLEVPEGR_456.8_356.2 C1S_HUMAN 29.14169137LIENGYFHPVK_439.6_343.2 F13B_HUMAN 28.63056809 EDTPNSVWEPAK_686.8_630.3C1S_HUMAN 28.61352686 AFTECCVVASQLR_770.9_673.4 CO5_HUMAN 28.57830281VNHVTLSQPK_374.9_459.3 B2MG_HUMAN 28.27203693VSFSSPLVAISGVALR_802.0_715.4 PAPP1_HUMAN 28.13008712DPDQTDGLGLSYLSSHIANVER_796.4_456.2 GELS_HUMAN 28.06549895VVGGLVALR_442.3_784.5 FA12_HUMAN 28.00684006NEIVFPAGILQAPFYTR_968.5_357.2 ECE1_HUMAN 27.97758456QVCADPSEEWVQK_788.4_275.2 CCL3_HUMAN 27.94276837 LQDAGVYR_461.2_680.3PD1L1_HUMAN 27.88063261 IQTHSTTYR_369.5_540.3 F13B_HUMAN 27.68873826TPSAAYLWVGTGASEAEK_919.5_849.4 GELS_HUMAN 27.66889639ALALPPLGLAPLLNLWAKPQGR_770.5_256.2 SHBG_HUMAN 27.63105727ALQDQLVLVAAK_634.9_289.2 ANGT_HUMAN 27.63097319 IEEIAAK_387.2_531.3CO5_HUMAN 27.52427934 TAVTANLDIR_537.3_288.2 CHL1_HUMAN 27.44246841VSEADSSNADWVTK_754.9_347.2 CFAB_HUMAN 27.43976782ITENDIQIALDDAK_779.9_873.5 APOB_HUMAN 27.39263522SSNNPHSPIVEEFQVPYNK_729.4_521.3 C15_HUMAN 27.34493617HPWIVHWDQLPQYQLNR_744.0_918.5 K56A3_HUMAN 27.19681613TPSAAYLWVGTGASEAEK_919.5_428.2 GELS_HUMAN 27.17319953AFLEVNEEGSEAAASTAVVIAGR_764.4_614.4 ANT3_HUMAN 27.10487351WGAAPYR_410.7_634.3 PGRP2_HUMAN 27.09930054IEVNESGTVASSSTAVIVSAR_693.0_545.3 PAI1_HUMAN 27.02567296AEAQAQYSAAVAK_654.3_908.5 ITIH4_HUMAN 26.98305259 VPLALFALNR_557.3_917.6PEPD_HUMAN 26.96988826 TLEAQLTPR_514.8_685.4 HEP2_HUMAN 26.94672621QALEEFQK_496.8_551.3 CO8B_HUMAN 26.67037155 WNFAYWAAHQPWSR_607.3_545.3PRG2_HUMAN 26.62600679 IYLQPGR_423.7_570.3 ITIH2_HUMAN 26.58752589FFQYDTWK_567.8_840.4 IGF2_HUMAN 26.39942037 NEIWYR_440.7_357.2FA12_HUMAN 26.35177282 GGEGTGYFVDFSVR_745.9_722.4 HRG_HUMAN 26.31688167VGEYSLYIGR_578.8_708.4 SAMP_HUMAN 26.17367498TAHISGLPPSTDFIVYLSGLAPSIR_871.5_800.5 TENA_HUMAN 26.13688183GVTGYFTFNLYLK_508.3_260.2 PSG5_HUMAN 26.06007032 DYWSTVK_449.7_620.3APOC3_HUMAN 26.03765187 YENYTSSFFIR_713.8_756.4 IL12B_HUMAN 25.9096605YGLVTYATYPK_638.3_334.2 CFAB_HUMAN 25.84440452 LFIPQITR_494.3_614.4PSG9_HUMAN 25.78081129 YEFLNGR_449.7_606.3 PLMN_HUMAN 25.17159874SEPRPGVLLR_375.2_454.3 FA7_HUMAN 25.16444381 NSDQEIDFK_548.3_294.2S10A5_HUMAN 25.12266401 YEVQGEVFTKPQLWP_911.0_293.1 CRP_HUMAN24.77595195 GVTGYFTFNLYLK_508.3_683.9 PSG5_HUMAN 24.75289081ISLLLIESWLEPVR_834.5_371.2 CSH_HUMAN 24.72379326 ALLLGWVPTR_563.3_373.2PAR4_HUMAN 24.68096599 VNHVTLSQPK_374.9_244.2 B2MG_HUMAN 24.53420489SGAQATWTELPWPHEK_613.3_793.4 HEMO_HUMAN 24.25610995AQPVQVAEGSEPDGFWEALGGK_758.0_623.4 GELS_HUMAN 24.18769142DLPHITVDR_533.3_490.3 MMP7_HUMAN 24.02606052 SEYGAALAWEK_612.8_788.4CO6_HUMAN 24.00163743 AVGYLITGYQR_620.8_523.3 PZP_HUMAN 23.93958524GFQALGDAADIR_617.3_717.4 TIMP1_HUMAN 23.69249513YEVQGEVFTKPQLWP_911.0_392.2 CRP_HUMAN 23.67764212 SDGAKPGPR_442.7_459.2COLI_HUMAN 23.63551614 GFQALGDAADIR_617.3_288.2 TIMP1_HUMAN 23.55832742IAPQLSTEELVSLGEK_857.5_533.3 AFAM_HUMAN 23.38139357DTDTGALLFIGK_625.8_217.1 PEDF_HUMAN 23.33375418LHEAFSPVSYQHDLALLR_699.4_380.2 FA12_HUMAN 23.27455931IYLQPGR_423.7_329.2 ITIH2_HUMAN 23.19122626

TABLE 38 Random Forest 32 Middle Window Variable UniProt_IDMeanDecreaseGini SEYGAALAWEK_612.8_788.4 CO6_HUMAN 2.27812193LLAPSDSPEWLSFDVTGVVR_730.1_430.3 TGFB1_HUMAN  2.080133179ALNHLPLEYNSALYSR_621.0_696.4 CO6_HUMAN  1.952233942ELPQSIVYK_538.8_417.7 FBLN3_HUMAN  1.518833357 VEHSDLSFSK_383.5_234.1B2MG_HUMAN  1.482593086 VFQFLEK_455.8_811.4 CO5_HUMAN  1.448810425VNHVTLSQPK_374.9_244.2 B2MG_HUMAN  1.389922815 YGIEEHGK_311.5_599.3CXA1_HUMAN  1.386794676 TLAFVR_353.7_492.3 FA7_HUMAN  1.371530925VLEPTLK_400.3_587.3 VTDB_HUMAN  1.368583173 VLEPTLK_400.3_458.3VTDB_HUMAN  1.336029064 DALSSVQESQVAQQAR_573.0_502.3 APOC3_HUMAN 1.307024357 AQPVQVAEGSEPDGFWEALGGK_758.0_574.3 GELS_HUMAN  1.282930911LHEAFSPVSYQHDLALLR_699.4_251.2 FA12_HUMAN 1.25362163SEPRPGVLLR_375.2_654.4 FA7_HUMAN  1.205539225 VEHSDLSFSK_383.5_468.2B2MG_HUMAN  1.201047302 SLDFTELDVAAEK_719.4_316.2 ANGT_HUMAN 1.189617326 SEYGAALAWEK_612.8_845.5 CO6_HUMAN  1.120706696TYLHTYESEI_628.3_515.3 ENPP2_HUMAN  1.107036657 VNHVTLSQPK_374.9_459.3B2MG_HUMAN  1.083264902 IEEIAAK_387.2_660.4 CO5_HUMAN  1.043635292ALNHLPLEYNSALYSR_621.0_538.3 CO6_HUMAN  0.962643698TLLPVSKPEIR_418.3_514.3 CO5_HUMAN  0.933440467 TEQAAVAR_423.2_615.4FA12_HUMAN  0.878933553 DLHLSDVFLK_396.2_260.2 CO6_HUMAN  0.816855601ALQDQLVLVAAK_634.9_289.2 ANGT_HUMAN  0.812620232 SLQAFVAVAAR_566.8_804.5IL23A_HUMAN  0.792274782 QGHNSVFLIK_381.6_260.2 HEMO_HUMAN  0.770830031ALQDQLVLVAAK_634.9_956.6 ANGT_HUMAN  0.767468246SLDFTELDVAAEK_719.4_874.5 ANGT_HUMAN  0.745827911

TABLE 39 Random Forest 100 Middle Window Variable UniProt_IDMeanDecreaseGini SEYGAALAWEK_612.8_788.4 CO6_HUMAN   1.241568411ALNHLPLEYNSALYSR_621.0_696.4 CO6_HUMAN   0.903126414LLAPSDSPEWLSFDVTGVVR_730._1430.3 TGFB1_HUMAN   0.846216563ANLINNIFELAGLGK_793.9_299.2 LCAP_HUMAN   0.748261193 VFQFLEK_455.8_811.4CO5_HUMAN   0.717545171 VEHSDLSFSK_383.5_234.1 B2MG_HUMAN   0.683219617ELPQSIVYK_538.8_417.7 FBLN3_HUMAN   0.671091545 LNIGYIEDLK_589.3_950.5PAI2_HUMAN   0.652293621 VLEPTLK_400.3_587.3 VTDB_HUMAN   0.627095631VNHVTLSQPK_374.9_244.2 B2MG_HUMAN   0.625773888 VLEPTLK_400.3_458.3VTDB_HUMAN   0.613655529 AQPVQVAEGSEPDGFWEALGGK_758.0_574.3 GELS_HUMAN  0.576305627 TLFIFGVTK_513.3_811.5 PSG4_HUMAN   0.574056825YGIEEHGK_311.5_599.3 CXA1_HUMAN   0.570270447 VPLALFALNR_557.3_620.4PEPD_HUMAN   0.556087614 EVFSKPISWEELLQ_852.9_376.2 FA40A_HUMAN  0.531461012 VEHSDLSFSK_383.5_468.2 B2MG_HUMAN   0.531214597TLAFVR_353.7_492.3 FA7_HUMAN  0.53070743 DALSSVQESQVAQQAR_573.0_502.3APOC3_HUMAN   0.521633041 SEYGAALAWEK__612.8_845.5 CO6_HUMAN  0.514509661 SLDFTELDVAAEK_719.4_316.2 ANGT_HUMAN  0.50489698SEPRPGVLLR_375.2_654.4 FA7_HUMAN 0.4824926LHEAFSPVSYQHDLALLR_699.4_251.2 FA12_HUMAN  0.48217238TYLHTYESEI_628.3_515.3 ENPP2_HUMAN   0.472286273AVDIPGLEAATPYR_736.9_399.2 TENA_HUMAN   0.470892051FSLVSGWGQLLDR_493.3_403.2 FA7_HUMAN   0.465839813GEVTYTTSQVSK_650.3_750.4 EGLN_HUMAN   0.458736205 VNHVTLSQPK_374.9_459.3B2MG_HUMAN   0.454348892 HFQNLGK_422.2_527.2 AFAM_HUMAN  0.45127405YGIEEHGK_311.5_341.2 CXA1_HUMAN   0.430641646

TABLE 40 Random Forest Protein Middle Window Variable UniProt_IDMeanDecreaseGini SEYGAALAWEK_ CO6_HUMAN 2.09649626 612.8_788.4LLAPSDSPEWLSF TGFB1_HUMAN 1.27664656 DVTGVVR_ 730.1_430.3 VFQFLEK_CO5_HUMAN 1.243884833 455.8_811.4 ANLINNIFELAG LCAP_HUMAN 1.231814882LGK_ 793.9_299.2 VEHSDLSFSK_ B2MG_HUMAN 1.188808078 383.5_234.1ELPQSIVYK_ FBLN3_HUMAN 1.185075445 538.8_417.7 LNIGYIEDLK_ PAI2_HUMAN1.122351536 589.3_950.5 VLEPTLK_ VTDB_HUMAN 1.062664798 400.3_458.3VPLALFALNR_ PEPD_HUMAN 1.019466776 557.3_620.4 TLAFVR_ FA7_HUMAN0.98797064 353.7_492.3 TLFIFGVTK_ PSG4_HUMAN 0.980159531 513.3_811.5AQPVQVAEGSEP GELS_HUMAN 0.960286027 DGFWEALGGK 758.0_574.3 DALSSVQESQVAAPOC3_HUMAN 0.947091926 QQAR_ 573.0_502.3 YGIEEHGK_ CXA1_HUMAN0.946937719 311.5_599.3 EVFSKPISWEELLQ_ FA40A_HUMAN 0.916262164852.9_376.2 LHEAFSPVSYQ FA12_HUMAN 0.891310053 HDLALLR_ 699.4_251.2SLDFTELDVAAEK_ ANGT_HUMAN 0.884498494 719.4_316.2 TYLHTYESEI_ENPP2_HUMAN 0.869043942 628.3_515.3 HFQNLGK_ AFAM_HUMAN 0.865435217422.2_527.2 AVDIPGLEAATPYR_ TENA_HUMAN 0.844842109 736.9_399.2 TLNAYDHR_PAR3_HUMAN 0.792615068 330.5_312.2 DVLLLVHNLPQNL PSG7_HUMAN 0.763629346TGHIWYK_ 791.8_310.2 GPITSAAELNDPQ EGLN_HUMAN 0.762305265 SILLR_632.4_826.5 VVLSSGSGPGLDL SHBG_HUMAN 0.706312721 PLVLGLPLQLK_791.5_598.4 SLQNASAIESILK_ IL3_HUMAN 0.645503581 687.4_860.5 HYINLITR_NPY_HUMAN 0.62631682 515.3_301.1 VELAPLPSWQPVGK_ ICAM1_HUMAN 0.608991877760.9_342.2 LQVNTPLVGASLLR_ BPIA1_HUMAN 0.607801279 741.0_925.6TLEAQLTPR_ HEP2_HUMAN 0.597771074 514.8_814.4 SDGAKPGPR_ COLI_HUMAN0.582773073 442.7_459.2

TABLE 41  Random Forest All Middle Window Variable UniProt IDMeanDecreaseGini SEYGAALAWEK_ CO6_HUMAN 0.493373282 612.8_788.4ALNHLPLEYNSAL CO6_HUMAN 0.382180772 YSR_ 621.0_696.4 VFQFLEK_ CO5_HUMAN0.260292083 455.8_811.4 LLAPSDSPEWLSFD TGFB1_HUMAN 0.243156718 VTGWR_730.1_430.3 NADYSYSVWK_ CO5_HUMAN 0.242388196 616.8_769.4 VLEPTLK_VTDB_HUMAN 0.238171849 400.3_458.3 VEHSDLSFSK_ B2MG_HUMAN 0.236873731383.5_234.1 ELPQSIVYK_ FBLN3_HUMAN 0.224727161 538.8_417.7 VLEPTLK_VTDB_HUMAN 0.222105614 400.3_587.3 TLFIFGVTK_ PSG4_HUMAN 0.210807574513.3_811.5 ANLINNIFELAGLGK_ LCAP_HUMAN 0.208714978 793.9_299.2LNIGYIEDLK_ PAI2_HUMAN 0.208027555 589.3_950.5 SEYGAALAWEK_ CO6_HUMAN0.197362212 612.8_845.5 VNHVTLSQPK_ B2MG_HUMAN 0.195728091 374.9_244.2YGIEEHGK_ CXA1_HUMAN 0.189969499 311.5_599.3 HFQNLGK_ AFAM_HUMAN0.189572857 422.2_527.2 AGITIPR_ IL17_HUMAN 0.188351054 364.2_486.3AQPVQVAEGSE GELS_HUMAN 0.185069517 PDGFWEALGGK_ 758.0_574.3SLDFTELDVAAEK_ ANGT_HUMAN 0.173688295 719.4_316.2 TLAFVR_ FA7_HUMAN0.170636045 353.7_492.3 SEPRPGVLLR_ FA7_HUMAN 0.170608352 375.2_654.4TLLIANETLR_ IL5_HUMAN 0.16745571 572.3_703.4 ALNHLPLEYNS CO6_HUMAN0.161514946 ALYSR_ 621.0_538.3 LHEAFSPVSYQ FA12_HUMAN 0.15852146HDLALLR_ 699.4_251.2 DGSPDVTTADI PGRP2_HUMAN 0.154028378 GANTPDATK_973.5_844.4 VPLALFALNR_ PEPD_HUMAN 0.153725879 557.3_620.4AVDIPGLEAATPYR_ TENA_HUMAN 0.150920884 736.9_399.2 YGIEEHGK_ CXA1_HUMAN0.150319671 311.5_341.2 FSLVSGWGQLLDR_ FA7_HUMAN 0.144781622 493.3_403.2IEEIAAK_ CO5_HUMAN 0.141983196 387.2_660.4

TABLE 42 Random Forest 32 Middle-Late Window Variable UniProt_IDMeanDecreaseGini VPLALFALNR_ PEPD_HUMAN 4.566619475 557.3_620.4 VFQFLEK_CO5_HUMAN 3.062474666 455.8_811.4 AQPVQVAEGSEP GELS_HUMAN 3.033740627DGFWEALGGK_ 758.0_574.3 LIEIANHVDK_ ADA12_HUMAN 2.825082394 384.6_498.3DALSSVQESQVA APOC3_HUMAN 2.787777983 QQAR_ 573.0_502.3 TLAFVR_ FA7_HUMAN2.730532075 353.7_492.3 ALNHLPLEYNSA CO6_HUMAN 2.671290375 LYSR_621.0_696.4 AVYEAVLR_ PEPD_HUMAN 2.621357053 460.8_587.4 SEPRPGVLLR_FA7_HUMAN 2.57568964 375.2_654.4 TYLHTYESEI_ ENPP2_HUMAN 2.516708906628.3_515.3 ALNHLPLEYNS CO6_HUMAN 2.497348374 ALYSR_ 621.0_538.3LIEIANHVDK_ ADA12_HUMAN 2.457401462 384.6_683.4 YGIEEHGK_ CXA1_HUMAN2.396824268 311.5_599.3 VLEPTLK_ VTDB_HUMAN 2.388105564 400.3_587.3SEYGAALAWEK_ CO6_HUMAN 2.340473883 612.8_788.4 WSAGLTSSQVD CBG_HUMAN2.332007976 LYIPK_ 883.0_515.3 FGFGGSTDSGPIR_ ADA12_HUMAN 2.325669514649.3_946.5 SEYGAALAWEK_ CO6_HUMAN 2.31761671 612.8_845.5 QINSYVK_CBG_HUMAN 2.245221163 426.2_496.3 QINSYVK_ CBG_HUMAN 2.212307699426.2_610.3 TEQAAVAR_ FA12_HUMAN 2.105860336 423.2_615.4 AVYEAVLR_PEPD_HUMAN 2.098321893 460.8_750.4 TEQAAVAR_ FA12_HUMAN 2.062684763423.2_487.3 DFNQFSSGEK_ FETA_HUMAN 2.05160689 386.8_333.2 SLQAFVAVAAR_IL23A_HUMAN 1.989521006 566.8_804.5 SLDFTELDVAAEK_ ANGT_HUMAN1.820628782 719.4_316.2 DPTFIPAPIQAK_ ANGT_HUMAN 1.763514326 433.2_556.3DPTFIPAPIQAK_ ANGT_HUMAN 1.760870392 433.2_461.2 VLEPTLK_ VTDB_HUMAN1.723389354 400.3_458.3 YENYTSSFFIR_ IL12B_HUMAN 1.63355187 713.8_756.4

TABLE 43 Random Forest 100 Middle-Late Window Variable UniProt_IDMeanDecreaseGini VPLALFALNR_ PEPD_HUMAN 1.995805024 557.3_620.4 VFQFLEK_CO5_HUMAN 1.235926416 455.8_811.4 DALSSVQESQVAQQAR_ APOC3_HUMAN1.187464899 573.0_502.3 EVFSKPISWEELLQ_ FA40A_HUMAN 1.166642578852.9_376.2 AQPVQVAEGSEPDGFW GELS_HUMAN 1.146077071 EALGGK_ 758.0_574.3TLAFVR_ FA7_HUMAN 1.143038275 353.7_492.3 ANLINNIFELAGLGK_ LCAP_HUMAN1.130656591 793.9_299.2 ALNHLPLEYNSALYSR_ CO6_HUMAN 1.098305298621.0_538.3 ELPQSIVYK_ FBLN3_HUMAN 1.096715712 538.8_417.7LLAPSDSPEWLSFDV TGFB1_HUMAN 1.086171713 TGWR_ 730.1_430.3 YGIEEHGK_CXA1_HUMAN 1.071880823 311.5_341.2 ALNHLPLEYNSALY CO6_HUMAN 1.062278869SR_ 621.0_696.4 TQILEWAAER_ EGLN_HUMAN 1.059019017 608.8_761.4 AVYEAVLR_PEPD_HUMAN 1.057920661 460.8_587.4 AEIEYLEK_ LYAM1_HUMAN 1.038388955497.8_552.3 SEPRPGVLLR_ FA7_HUMAN 1.028275728 375.2_654.4AVDIPGLEAATPYR_ TENA_HUMAN 1.026032369 736.9_399.2 LIEIANHVDK_ADA12_HUMAN 1.015065282 384.6_498.3 YGIEEHGK_ CXA1_HUMAN 0.98667651311.5_599.3 VLEPTLK_ VTDB_HUMAN 0.970330675 400.3_587.3 DVLLLVHNLPQNLTPSG7_HUMAN 0.934747674 GHIWYK_ 791.8_883.0 TAHISGLPPSTDFI TENA_HUMAN0.889111923 VYLSGLAPSIR_ 871.5_472.3 TLNAYDHR_ PAR3_HUMAN 0.887605636330.5_312.2 FGFGGSTDSGPIR_ ADA12_HUMAN 0.884305889 649.3_946.5LIEIANHVDK_ ADA12_HUMAN 0.880889836 384.6_683.4 SEYGAALAWEK_ CO6_HUMAN0.863585472 612.8_788.4 TYLHTYESEI_ ENPP2_HUMAN 0.849232356 628.3_515.3FGFGGSTDSGPIR_ ADA12_HUMAN 0.843334824 649.3_745.4 SEYGAALAWEK_CO6_HUMAN 0.842319271 612.8_845.5 TPSAAYLWVGTGA GELS_HUMAN 0.828959173SEAEK_ 919.5_849.4

TABLE 44 Random Forest Protein Middle-Late Window Variable UniProt_IDMeanDecreaseGini VPLALFALNR_ PEPD_HUMAN 3.202123047 557.3_620.4ANUNNIFELAGLGK_ LCAP_HUMAN 2.100447309 793.9_299.2 VFQFLEK_ CO5_HUMAN2.096157529 455.8_811.4 AQPVQVAEGSEP GELS_HUMAN 2.052960939 DGFWEALGGK_758.0_574.3 ALNHLPLEYNSAL CO6_HUMAN 2.046139797 YSR_ 621.0_696.4TQILEWAAER_ EGLN_HUMAN 1.99287941 608.8_761.4 ELPQSIVYK_ FBLN3_HUMAN1.920894959 538.8_417.7 TGVAVNKPAEFTV FLNA_HUMAN 1.917665697 DAK_549.6_258.1 SEPRPGVLLR_ FA7_HUMAN 1.883557705 375.2_654.4 DALSSVQESQVAQAPOC3_HUMAN 1.870232155 QAR_ 573.0_502.3 EVFSKPISWEELL FA40A_HUMAN1.869000136 Q_852.9_376.2 LIEIANHVDK_ ADA12_HUMAN 1.825457092384.6_683.4 VLEPTLK_ VTDB_HUMAN 1.695327774 400.3_587.3 TEQAAVAR_FA12_HUMAN 1.685013152 423.2_615.4 LLAPSDSPEWLS TGFB1_HUMAN 1.684068039FDVTGWR_ 730.1_430.3 TLNAYDHR_ PAR3_HUMAN 1.673758239 330.5_312.2AVDIPGLEAATP TENA_HUMAN 1.648896853 YR_ 736.9_399.2 DVLLLVHNLPQNPSG7_HUMAN 1.648146088 LTGHIWYK_ 791.8_883.0 AEIEYLEK_ LYAM1_HUMAN1.645833005 497.8_552.3 TYLHTYESEI_ ENPP2_HUMAN 1.639121965 628.3_515.3AGLLRPDYALLG PGRP2_HUMAN 1.610227875 HR_ 518.0_595.4 YGIEEHGK_CXA1_HUMAN 1.606978339 311.5_599.3 QINSYVK_ CBG_HUMAN 1.554905578426.2_496.3 LTTVDIVTLR_ IL2RB_HUMAN 1.484081016 565.8_815.5AALAAFNAQNNGS FETUA_HUMAN 1.43173022 NFQLEEISR_ 789.1_746.4AEVIWTSSDHQVL PD1L1_HUMAN 1.394857397 SGK_ 586.3_300.2 ALEQDLPVNIK_CNDP1_HUMAN 1.393464547 620.4_570.4 DFNQFSSGEK_ FETA_HUMAN 1.374296237386.8_333.2 TSYQVYSK_ C163A_HUMAN 1.36141387 488.2_787.4 TLEAQLTPR_HEP2_HUMAN 1.311118611 514.8_685.4

TABLE 45 Random Forest All Middle-Late Window Variable UniProt_IDMeanDecreaseGini VPLALFALNR_ PEPD_HUMAN 0.685165163 557.3_620.4 VFQFLEK_CO5_HUMAN 0.426827804 455.8_811.4 ALNHLPLEYNSA CO6_HUMAN 0.409942379LYSR_ 621.0_538.3 YGIEEHGK_ CXA1_HUMAN 0.406589512 311.5_341.2ALNHLPLEYNSA CO6_HUMAN 0.402152062 LYSR_ 621.0_696.4 AQPVQVAEGSEPGELS_HUMAN 0.374861014 DGFWEALGGK_ 758.0_574.3 ANLINNIFELAG LCAP_HUMAN0.367089422 LGK_ 793.9_299.2 TQILEWAAER_ EGLN_HUMAN 0.353757524608.8_761.4 AVYEAVLR_ PEPD_HUMAN 0.350518668 460.8_587.4 TLAFVR_FA7_HUMAN 0.344669505 353.7_492.3 SEPRPGVLLR_ FA7_HUMAN 0.338752336375.2_654.4 LIEIANHVDK_ ADA12_HUMAN 0.321850027 384.6_683.4 ELPQSIVYK_FBLN3_HUMAN 0.301819017 538.8_417.7 EVFSKPISWEEL FA40A_HUMAN 0.299561811LQ_ 852.9_376.2 LIEIANHVDK_ ADA12_HUMAN 0.298253589 384.6_498.3 VLEPTLK_VTDB_HUMAN 0.296206088 400.3_587.3 YGIEEHGK_ CXA1_HUMAN 0.295621408311.5_599.3 DVLLLVHNLPQN PSG7_HUMAN 0.292937475 LTGHIWYK_ 791.8_883.0TYLHTYESEI_ ENPP2_HUMAN 0.275902848 628.3_515.3 DALSSVQESQVA APOC3_HUMAN0.275664578 QQAR_ 573.0_502.3 FGFGGSTDSG ADA12_HUMAN 0.27120436 PIR_649.3_745.4 AVDIPGLEAAT TENA_HUMAN 0.266568271 PYR_ 736.9_399.2TGVAVNKPAEFT FLNA_HUMAN 0.262537889 VDAK_ 549.6_258.1 TLNAYDHR_PAR3_HUMAN 0.259901193 330.5_312.2 IYLQPGR_ ITIH2_HUMAN 0.259086112423.7_329.2 AEVIWTSSDHQV PD1L1_HUMAN 0.25722354 LSGK_ 586.3_300.2VPSHAVVAR_ TRFL_HUMAN 0.256151812 312.5_515.3 SEYGAALAWEK_ CO6_HUMAN0.251704855 612.8_845.5 FGFGGSTDSGPIR_ ADA12_HUMAN 0.249400642649.3_946.5 SEYGAALAWEK_ CO6_HUMAN 0.245930393 612.8_788.4

TABLE 46 Random Forest 32 Late Window Variable UniProt_DMeanDecreaseGini AVYEAVLR_ PEPD_HUMAN 1.889521223 460.8_587.4 AEIEYLEK_LYAM1_HUMAN 1.75233545 497.8_552.3 AALAAFNAQNNGS FETUA_HUMAN 1.676813493NFQLEEISR_ 789.1_746.4 TGVAVNKPAEFTV FLNA_HUMAN 1.600684153 DAK_549.6_258.1 AVYEAVLR_ PEPD_HUMAN 1.462889662 460.8_750.4 LIEIANHVDK_ADA12_HUMAN 1.364115361 384.6_683.4 VPLALFALNR_ PEPD_HUMAN 1.324317148557.3_620.4 QINSYVK_ CBG_HUMAN 1.305932064 426.2_610.3 ITQDAQLK_CBG_HUMAN 1.263533228 458.8_702.4 FGFGGSTDSGPIR_ ADA12_HUMAN 1.245153376649.3_745.4 LIEIANHVDK_ ADA12_HUMAN 1.236529173 384.6_498.3 QINSYVK_CBG_HUMAN 1.221866266 426.2_496.3 YSHYNER_ HABP2_HUMAN 1.169575572323.5_418.2 YYGYTGAFR_ TRFL_HUMAN 1.126684146 549.3_450.3 VGVISFAQK_TFR2_HUMAN 1.075283855 474.8_580.3 VFQYIDLHQDEFV CNDP1_HUMAN 1.07279097QTLK_ 708.4_375.2 SPEAEDPLGVER_ Z512B_HUMAN 1.05759256 649.8_314.1DEIPHNDIALLK_ HABP2_HUMAN 1.028933332 459.9_510.8 ALEQDLPVNIK_CNDP1_HUMAN 1.014443799 620.4_798.5 ALEQDLPVNIK_ CNDP1_HUMAN 1.010573267620.4_570.4 ILDGGNK_ CXCL5_HUMAN 0.992175141 358.7_603.3 TSYQVYSK_C163A_HUMAN 0.95649585 488.2_787.4 YENYTSSFFIR_ IL12B_HUMAN 0.955085198713.8_756.4 SETEIHQGFQHL CBG_HUMAN 0.944726739 HQLFAK_ 717.4_447.2TLPFSR_ LYAM1_HUMAN 0.944426109 360.7_506.3 VLSSIEQK_ 1433S_HUMAN0.933902495 452.3_691.4 AEIEYLEK_ LYAM1_HUMAN 0.891235263 497.8_389.2GTYLYNDCPGPG TNR1A_HUMAN 0.87187037 QDTDCR_ 697.0_666.3 SGVDLADSNQK_VGFR3_HUMAN 0.869821307 567.3_662.3 SGVDLADSNQK_ VGFR3_HUMAN 0.839946466567.3_591.3

TABLE 47 Random Forest 100 Late Window Variable UniProt_IDMeanDecreaseGini AVYEAVLR_ PEPD_HUMAN 0.971695767 460.8_587.4 AEIEYLEK_LYAM1_HUMAN 0.920098693 497.8_552.3 TGVAVNKPAEFTVDAK_ FLNA_HUMAN0.786924487 549.6_258.1 AVYEAVLR_ PEPD_HUMAN 0.772867983 460.8_750.4AALAAFNAQNNGSNFQ FETUA_HUMAN 0.744138513 LEEISR_ 789.1_746.4 AYSDLSR_SAMP_HUMAN 0.736078079 406.2_375.2 VPLALFALNR_ PEPD_HUMAN 0.681784822557.3_620.4 QINSYVK_ CBG_HUMAN 0.585819307 426.2_610.3 LIEIANHVDK_ADA12_HUMAN 0.577161158 384.6_498.3 FGFGGSTDSGPIR_ ADA12_HUMAN0.573055613 649.3_745.4 WSAGLTSSQVDLY CBG_HUMAN 0.569156128 IPK_883.0_515.3 ITQDAQLK_ CBG_HUMAN 0.551017844 458.8_702.4 LIEIANHVDK_ADA12_HUMAN 0.539330047 384.6_683.4 YYGYTGAFR_ TRFL_HUMAN 0.527652175549.3_450.3 VFQYIDLHQDEFV CNDP1_HUMAN 0.484155289 QTLK_ 708.4_375.2FQLPGQK_ PSG1_HUMAN 0.480394031 409.2_429.2 AVDIPGLEAATPYR_ TENA_HUMAN0.475252565 736.9_286.1 QINSYVK_ CBG_HUMAN 0.4728541 426.2_496.3YISPDQLADLYK_ ENOAHUMAN 0.470079977 713.4_277.2 TLPFSR_ LYAM1_HUMAN0.46881451 360.7_506.3 SPEAEDPLGVER_ Z512B_HUMAN 0.4658941 649.8_314.1ALEQDLPVNIK_ CNDP1_HUMAN 0.463604174 620.4_798.5 YSHYNER_ HABP2_HUMAN0.453076307 323.5_418.2 VGVISFAQK_ TFR2_HUMAN 0.437768219 474.8_580.3LQDAGVYR_ PD1L1_HUMAN 0.428524689 461.2_680.3 AEIEYLEK_ LYAM1_HUMAN0.42041448 497.8_389.2 TSYQVYSK_ C163A_HUMAN 0.419411932 488.2_787.4SVVLIPLGAVDD CNDP1_HUMAN 0.415325735 GEHSQNEK_ 703.0_798.4 ALEQDLPVNIK_CNDP1_HUMAN 0.407951733 620.4_570.4 ILDGGNK_ CXCL5_HUMAN 0.401059572358.7_603.3

TABLE 48 Random Forest Protein Late Window Variable UniProt_DMeanDecreaseGini AVYEAVLR_ PEPD_HUMAN 1.836010146 460.8_587.4 AEIEYLEK_LYAM1_HUMAN 1.739802548 497.8_552.3 AALAAFNAQNNG FETUA_HUMAN 1.455337749SNFQ LEEISR_ 789.1_746.4 TGVAVNKPAEFT FLNA_HUMAN 1.395043941 VDAK_549.6_258.1 AYSDLSR_ SAMP_HUMAN 1.177349958 406.2_375.2 LIEIANHVDK_ADA12_HUMAN 1.14243936 384.6_683.4 QINSYVK_ CBG_HUMAN 1.05284482426.2_496.3 ALEQDLPVNIK_ CNDP1_HUMAN 0.971678206 620.4_798.5YISPDQLADLYK_ ENOA_HUMAN 0.902293734 713.4_277.2 AVDIPGLEAATP TENA_HUMAN0.893163413 YR_ 736.9_286.1 SPEAEDPLGVER_ Z512B_HUMAN 0.856551531649.8_314.1 ILDGGNK_ CXCL5_HUMAN 0.841485153 358.7_603.3 VGVISFAQK_TFR2_HUMAN 0.835256078 474.8_580.3 YYGYTGAFR_ TRFL_HUMAN 0.831195917549.3_450.3 YSHYNER_ HABP2_HUMAN 0.814479968 323.5_418.2 FQLPGQK_PSG1_HUMAN 0.77635168 409.2_276.1 YENYTSSFFIR_ IL12B_HUMAN 0.761241391713.8_756.4 TEQAAVAR_ FA12_HUMAN 0.73195592 423.2_615.4 SGVDLADSNQK_VGFR3_HUMAN 0.72504131 567.3_662.3 VLSSIEQK_ 1433S_HUMAN 0.713380314452.3_691.4 GTYLYNDCPGPGQ TNR1A_HUMAN 0.704248586 DTDCR_ 697.0_666.3TSYQVYSK_ C163A_HUMAN 0.69026345 488.2_787.4 TLEAQLTPR_ HEP2_HUMAN0.654641588 514.8_685.4 AEVIWTSSDHQV PD1L1_HUMAN 0.634751081 LSGK_586.3_300.2 TAVTANLDIR_ CHL1_HUMAN 0.619871203 537.3_288.2ITENDIQIALDDAK_ APOB_HUMAN 0.606313398 779.9_632.3 TASDFITK_ GELS_HUMAN0.593535076 441.7_781.4 SPQAFYR_ REL3_HUMAN 0.592004045 434.7_556.3NHYTESISVAK_ NEUR1_HUMAN 0.588383911 624.8_415.2 LTTVDIVTLR_ IL2RB_HUMAN0.587343951 565.8_815.5

Random Forest All Late Window Variable UniProt_ID MeanDecreaseGiniAVYEAVLR_ PEPD_HUMAN 0.437300283 460.8_587.4 AEIEYLEK_ LYAM1_HUMAN0.371624293 497.8_552.3 AALAAFNAQNNG FETUA_HUMAN 0.304039734 SNFQLEEISR_789.1_746.4 TGVAVNKPAEFT FLNA_HUMAN 0.280588526 VDAK_ 549.6_258.1AVYEAVLR_ PEPD_HUMAN 0.266788699 460.8_750.4 AYSDLSR_ SAMP_HUMAN0.247412666 406.2_375.2 VPLALFALNR_ PEPD_HUMAN 0.229955358 557.3_620.4LIEIANHVDK_ ADA12_HUMAN 0.218186524 384.6_683.4 ITQDAQLK_ CBG_HUMAN0.217646659 458.8_702.4 WSAGLTSSQVD_ CBG_HUMAN 0.213840705 LYIPK_883.0_515.3 FGFGGSTDSGPIR_ ADA12_HUMAN 0.212794469 649.3_745.4LIEIANHVDK_ ADA12_HUMAN 0.208620264 384.6_498.3 QINSYVK_ CBG_HUMAN0.202054546 426.2_610.3 QINSYVK_ CBG_HUMAN 0.197235139 426.2_496.3FQLPGQK_ PSG1_HUMAN 0.188311102 409.2_429.2 VFQYIDLHQDEFVQ CNDP1_HUMAN0.180534913 TLK_ 708.4_375.2 ALEQDLPVNIK_ CNDP1_HUMAN 0.178464358620.4_798.5 YYGYTGAFR_ TRFL_HUMAN 0.176050092 549.3_450.3ALFLDALGPPAVTR_ INHA_HUMAN 0.171492975 720.9_640.4 FQLPGQK_ PSG1_HUMAN0.167576198 409.2_276.1 SETEIHQGFQHL CBG_HUMAN 0.162231844 HQLFAK_717.4_447.2 ALEQDLPVNIK_ CNDP1_HUMAN 0.162165399 620.4_570.4 VPSHAVVAR_TRFL_HUMAN 0.156742065 312.5_515.3 AVDIPGLEAATPYR_ TENA_HUMAN0.153681405 736.9_286.1 FTFTLHLETPKPS PSG1_HUMAN 0.152042057 ISSSNLNPR_829.4_874.4 VGVISFAQK_ TFR2_HUMAN 0.149034355 474.8_580.3 TLPFSR_LYAM1_HUMAN 0.143223501 360.7_506.3 SLDFTELDVAAEK_ ANGT_HUMAN0.141216186 719.4_874.5 SPEAEDPLGVER_ Z512B_HUMAN 0.139843479649.8_314.1 YGIEEHGK_ CXA1_HUMAN 0.135236953 311.5_341.2

TABLE 50 Selected Transitions for Early Window Transition Parent ProteinLIQDAVTGLTVNGQI ITIH3_HUMAN TGDK_ 972.0_798.4 VQTAHFK_ CO8A_HUMAN277.5_431.2 FLNWIK_ HABP2_HUMAN 410.7_560.3 ITGFLKPGK_ LBP_HUMAN320.9_429.3 ALNHLPLEYNSALYSR_ CO6_HUMAN 621.0_538.3 TYLHTYESEI_ENPP2_HUMAN 628.3_908.4 LIENGYFHPVK_ F13B_HUMAN 439.6_627.4 AVLH1GEK_THBG_HUMAN 289.5_292.2 QALEEFQK_ CO8B_HUMAN 496.8_680.3 TEFLSNYLTNVDDITLENPP2_HUMAN VPGTLGR_ 846.8_600.3 TASDFITK_ GELS_HUMAN 441.7_781.4LPNNVLQEK_ AFAM_HUMAN 527.8_844.5 AHYDLR_ FETUA_HUMAN 387.7_288.2ITLPDFTGDLR_ LBP_HUMAN 624.3_288.2 IEGNLIFDPNNYLPK_ APOB_HUMAN874.0_414.2 ITGFLKPGK_ LBP_HUMAN 320.9_301.2 FSVVYAK_ FETUA_HUMAN407.2_381.2 ITGFLKPGK_ LBP_HUMAN 320.9_429.3 VFQFLEK_ CO5_HUMAN455.8_811.4 LIQDAVTGLTVNGQI ITIH3_HUMAN TGDK_ 972.0_798.4 DADPDTFFAK_AFAM_HUMAN 563.8_825.4

TABLE 51 Selected Proteins for Early Window Protein complement componentC6 precursor CO6_HUMAN inter-alpha-trypsin inhibitor heavy chain H3ITIH3_HUMAN preproprotein Coagulation factor XIII B chain F13B_HUMANEctonucleotide pyrophosphatase/phosphodiesterase ENPP2_HUMAN familymember 2 Complement component C8 beta chain CO8B_HUMAN thyroxine-bindingglobulin precursor THBG_HUMAN Hyaluronan-binding protein 2 HABP2_HUMANlipopolysaccharide-binding protein LBP_HUMAN Complement factor BCFAB_HUMAN Gelsolin GELS_HUMAN afamin precursor AFAM_HUMANapolipoprotein B-100 precursor APOB_HUMAN complement component C5CO5_HUMAN Alpha-2-HS-glycoprotein FETUA_HUMAN complement component C8gamma chain CO8G_HUMAN

TABLE 52 Selected Transitions for Middle-Late Window TransitionPatent Protein VPLALFALNR_ PEPD_HUMAN 557.3_620.4 VFQFLEK_ CO5_HUMAN455.8_811.4 AQPVQVAEGSEPDGF GELS_HUMAN WEALGGK_ 758.0_574.3 LIEIANHVDK_ADA12_HUMAN 384.6_498.3 TLAFVR_ FA7_HUMAN 353.7_492.3 ALNHLPLEYNSALYSR_CO6_HUMAN 621.0_696.4 AVYEAVLR_ PEPD_HUMAN 460.8_587.4 SEPRPGVLLR_FA7_HUMAN 375.2_654.4 TYLHTYESEI_ ENPP2_HUMAN 628.3_515.3ALNHLPLEYNSALYSR_ CO6_HUMAN 621.0_538.3

TABLE 53 Selected Proteins for Middle-Late Window Protein Xaa-Prodipeptidase PEPD_HUMAN Leucyl-cystinyl aminopeptidase LCAP_HUMANcomplement component C5 CO5__HUMAN Gelsolin GELS_HUMAN complementcomponent C6 precursor CO6_HUMAN Endoglin precursor EGLN_HUMANEGF-containing fibulin-like extracellular matrix FBLN3_HUMAN protein 1coagulation factor VII isoform a FA7_HUMAN Disintegrin andmetalloproteinase domain-containing ADA12_HUMAN protein 12 vitaminD-binding protein isoform 1 precursor VTDB_HUMAN coagulation factor XIIprecursor FA12_HUMAN Corticosteroid-binding globulin CBG_HUMAN

Example 6. Study V to Further Refine Preterm Birth Biomarkers

A additional hypothesis-dependent discovery study was performed with afurther refined scheduled MRM assay. Less robust transitions were againremoved to improve analytical performance and make room for theinclusion of stable-isotope labeled standards (SIS) corresponding to 79analytes of interest identified in previous studies. SIS peptides haveidentical amino acid sequence, chromatographic and MS fragmentationbehaviour as their endogenous peptide counterparts, but differ in mass.Therefore they can be used to reduce LC-MS analytical variability andconfirm analyte identity. Samples included approximately 60 spontaneousPTB cases (delivery at less than 37 weeks, 0 days), and 180 termcontrols (delivery at greater than or equal to 37 weeks, 0 days). Eachcase was designated a “matched” control to within one day of blood drawand two “random” controls matched to the same 3 week blood draw window(17-19, 20-22 or 23-25 weeks gestation). For the purposes of analysisthese three blood draw windows were combined. Samples were processedessentially as described previously, except that in this study, trypticdigests were reconstituted in a solution containing SIS standards. Rawanalyte peak areas were Box-Cox transformed, corrected for run order andbatch effects by regression and used for univariate and multivariatestatistical analyses. Univariate analysis included determination ofp-values for adjusted peak areas for all analytes from t-testsconsidering cases vs controls defined as either deliveries at >37 weeks(Table 54) or deliveries at >40 weeks (Table 55). Univariate analysisalso included the determination of p-values for a linear model thatevaluates the dependence of each analyte's adjusted peak area on thetime to birth (gestational age at birth minus the gestational age atblood draw) (Table 56) and the gestational age at birth (Table 57).Additionally raw peak area ratios were calculated for endogenousanalytes and their corresponding SIS counterparts, Box-Cox transformedand then used for univariate and multivariate statistical analyses. Theabove univariate analysis was repeated for analyte/SIS peak area ratiovalues, summarized in Tables 58-61, respectively.

Multivariate random forest regression models were built using analytevalues and clinical variables (e.g. Maternal age, (MAGE), Body massindex, (BMI)) to predict Gestational Age at Birth (GAB). The accuracy ofthe random forest was evaluated with respect to correlation of thepredicted and actual GAB, and with respect to the mean absolutedeviation (MAD) of the predicted from actual GAB. The accuracy wasfurther evaluated by determining the area under the receiver operatingcharacteristic curve (AUC) when using the predicted GAB as aquantitative variable to classify subjects as full term or pre-term.Random Forest Importance Values were fit to an Empirical CumulativeDistribution Function and probabilities (P) were calculated. We reportthe analytes by importance ranking (P>0.7) in the random forest models,using adjusted analyte peak area values (Table 62) and analyte/SIS peakarea ratio values (Table 63).

The probability of pre-term birth, p(PTB), may be estimated using thepredicted gestational age at birth (GAB) as follows. The estimate willbe based on women enrolled in the Sera PAPR clinical trial, whichprovided the subjects used to develop the PTB prediction methods.

Among women with a predicted GAB of j days plus or minus k days, p(PTB)was estimated as the proportion of women in the PAPR clinical trial witha predicted GAB of j days plus or minus k days who actually deliverbefore 37 weeks gestational age.

More generally, for women with a predicted GAB of j days plus or minus kdays, the probability that the actual gestational age at birth will beless than a specified gestational age, p(actual GAB<specified GAB), wasestimated as the proportion of women in the PAPR clinical trial with apredicted GAB of j days plus or minus k days who actually deliver beforethe specified gestational age. FIG. 1 depicts a scatterplot of actualgestational age at birth versus predicted gestational age from randomforest regression model. FIG. 2 shows the distribution of predictedgestational age from random forest regression model versus actualgestational age at birth (GAB), where actual GAB was given in categoriesof (i) less than 37 weeks, (ii) 37 to 39 weeks, and (iii) 40 weeks orgreater.

TABLE 54 Univariate p-values for Ad_usted Peak Areas (<37 vs >37 weeks)Transition Protein pvalue SPELQAEAK_ APOA2_HUMAN 0.00246566 486.8_659.4ALALPPLGLAPLLNLW SHBG_HUMAN 0.002623332 AKPQGR_ 770.5_457.3ALALPPLGLAPLLNLW SHBG_HUMAN 0.002822593 AKPQGR_ 770.5_256.2 SPELQAEAK_APOA2_HUMAN 0.003183869 486.8_788.4 VVLSSGSGPGLDLPLVL SHBG_HUMAN0.004936049 GLPLQLK_ 791.5_768.5 VVLSSGSGPGLDLPLVL SHBG_HUMAN0.005598977 GLPLQLK_ 791.5_598.4 DYWSTVK_ APOC3_HUMAN 0.005680405449.7_347.2 DYWSTVK_ APOC3_HUMAN 0.006288693 449.7_620.3 WGAAPYR_PGRP2_HUMAN 0.006505238 410.7_634.3 DALSSVQESQVAQQAR_ APOC3_HUMAN0.007626246 573.0_502.3 DALSSVQESQVAQQAR_ APOC3_HUMAN 0.008149335573.0_672.4 LSIPQITTK_ PSG5_HUMAN 0.009943955 500.8_687.4 GWVTDGFSSLK_APOC3_HUMAN 0.010175055 598.8_854.4 IALGGLLFPASNLR_ SHBG_HUMAN0.010784167 481.3_657_4 AKPALEDLR_ APOA1_HUMAN 0.011331968 506.8_813.5WGAAPYR_ PGRP2_HUMAN 0.011761088 410.7_577.3 VPLALFALNR_ PEPD_HUMAN0.014050395 557.3_620.4 FSLVSGWGQLLDR_ FA7_HUMAN 0.014271151 493.3_447.3LSIPQITTK_ PSG5_HUMAN 0.014339942 500.8_800.5 TLAFVR_ FA7_HUMAN0.014459876 353.7_274_2 DVLLLVHNLPQNLPGY PSG9_HUMAN 0.016720007 FWYK_810.4_960.5 FSVVYAK_ FETUA_HUMAN 0.016792786 407.2_381.2DVLLLVHNLPQNLPGY PSG9_HUMAN 0.017335929 FWYK_ 810.4_215.1 SEPRPGVLLR_FA7_HUMAN 0.018147773 375.2_654.4 ALNHLPLEYNSALYSR_ CO6_HUMAN0.019056484 621.0_538.3 WNFAYWAAHQPWSR_ PRG2_HUMAN 0.019190043607.3_545.3 ALNHLPLEYNSALYSR_ CO6_HUMAN 0.020218682 621.0_696.4AQPVQVAEGSEPDGFW GELS_HUMAN 0.020226218 EALGGK_ 758.0_623.4 GWVTDGFSSLK_APOC3_HUMAN 0.023192703 598.8_953.5 IALGGLLFPASNLR_ SHBG_HUMAN0.02391691 481.3_412.3 WNFAYWAAHQPWSR_ PRG2_HUMAN 0.026026975607.3_673.3 FGFGGSTDSGPIR_ ADA12_HUMAN 0.027731407 649.3_745.4SEYGAALAWEK_ CO6_HUMAN 0.031865281 612.8_788.4 DADPDTFFAK_ AFAM_HUMAN0.0335897 563.8_302.1 LFIPQITR_ PSG9_HUMAN 0.034140767 494.3_614.4DVLLLVHNLPQNLP PSG9_HUMAN 0.034653304 GYFWYK_ 810.4_328.2 TLAFVR_FA7_HUMAN 0.036441189 353.7_492.3 AVLHIGEK_ THBG_HUMAN 0.038539433289.5_292.2 IHPSYTNYR_ PSG2_HUMAN 0.039733019 384.2_452.2AGLLRPDYALLGHR_ PGRP2_HUMAN 0.040916226 518.0_369.2 ILILPSVTR_PSGx_HUMAN 0.042460036 506.3_559.3 YYLQGAK_ ITIH4_HUMAN 0.044511962421.7_516.3 TPSAAYLWVGTGAS GELS_HUMAN 0.046362381 EAEK_ 919.5_849.4AGLLRPDYALLGHR_ PGRP2_HUMAN 0.046572355 518.0_595.4 TYLHTYESEI_ENPP2_HUMAN 0.04754503 628.3_908.4 FSLVSGWGQLLDR_ FA7_HUMAN 0.048642964493.3_403_2 VNFTEIQK_ FETA_HUMAN 0.04871392 489.8_765.4 LFIPQITR_PSG9_HUMAN 0.040288923 494.3_727.4 DISEVVTPR_ CFAB_HUMAN 0.049458374508.3_787.4 SEPRPGVLLR_ FA7_HUMAN 0.049567047 375.2_454_3

Univariate p-values for Ad_usted Peak Areas (<37 vs >40 weeks)Transition Protein pvalue SPELQAEAK_ APOA2_HUMAN 0.001457796 486.8_659.4DYWSTVK_ APOC3_HUMAN 0.001619622 449.7_347.2 DYWSTVK_ APOC3_HUMAN0.002068704 449.7_620.3 DALSSVQESQVAQQAR_ APOC3_HUMAN 0.00250563573.0_502.3 GWVTDGFSSLK_ APOC3_HUMAN 0.002543943 598.8_854.4 SPELQAEAK_APOA2_HUMAN 0.003108814 486.8_788.4 SEPRPGVLLR_ FA7_HUMAN 0.004035832375.2_654.4 DALSSVQESQVAQQAR_ APOC3_HUMAN 0.00434652 573.0_672.4SEYGAALAWEK_ CO6_HUMAN 0.005306924 612.8_788.4 GWVTDGFSSLK_ APOC3_HUMAN0.005685534 598.8_953.5 ALNHLPLEYNSALYSR_ CO6_HUMAN 0.005770384621.0_696.4 TYLHTYESEI_ ENPP2_HUMAN 0.005798991 628.3_515.3ENPAVIDFELAPIVDLVR_ CO6_HUMAN 0.006248095 670.7_601.4 ALNHLPLEYNSALYSR_CO6_HUMAN 0.006735817 621.0_538.3 TYLHTYESEI_ ENPP2_HUMAN 0.007351774628.3_908.4 AGLLRPDYALLGF1R_ PGRP2_HUMAN 0.009541521 518_0_369.2AKPALEDLR_ APOA1_HUMAN 0.009780371 506.8_813.5 SEYGAALAWEK_ CO6_HUMAN0.010085363 612.8_845.5 FSLVSGWGQLLDR_ FA7_HUMAN 0.010401836 493.3_447.3WGAAPYR_ PGRP2_HUMAN 0.011233623 410.7_634.3 ENPAVIDFELAPIVDLVR_CO6_HUMAN 0.012029564 670.7_811.5 DVLLLVHNLPQNLPGYFWYK_ PSG9_HUMAN0.014808277 810_4_215.1 LFIPQITR_ PSG9_HUMAN 0.015879755 494.3_614.4WGAAPYR_ PGRP2_HUMAN 0.016562435 410.7_577.3 AGLLRPDYALLGHR_ PGRP2_HUMAN0.016793521 518_0_595.4 TLAFVR_ FA7_HUMAN 0.016919708 353.7_492.3FSLVSGWGQLLDR_ FA7_HUMAN 0.016937583 493.3_403.2 WWGGQPLWITATK_ENPP2_HUMAN 0.019050115 772.4_373.2 GYVIIKPLVWV_ SAMP_HUMAN 0.019675317643.9_304.2 DVLLLVHNLPQNLPG PSG9_HUMAN 0.020387647 YFWYK_ 810.4_960.5FGFGGSTDSGPIR_ ADA12_HUMAN 0.020458335 649.3_745.4 DVLLLVHNLPQNLPPSG9_HUMAN 0.021488084 GYFWYK_ 810.4_328.2 WWGGQPLWITATK_ ENPP2_HUMAN0.021709354 772.4_929.5 LDFHFSSDR_ INHBC_HUMAN 0.022403383 375.2_448.2LFIPQITR_ PSG9_HUMAN 0.025561103 494.3_727.4 TEFLSNYLTNVDDI ENPP2_HUMAN0.029344366 TLVPGTLGR_ 846.8_600.3 LSIPQITTK_ PSG5_HUMAN 0.031361776500.8_800.5 ALVLELAK_ INHBE_HUMAN 0.031690737 428.8_672.4 SEPRPGVLLR_FA7_HUMAN 0.033067953 375.2_454.3 LSIPQITTK_ PSG5_HUMAN 0.033972449500.8_687.4 LDFHFSSDR_ INHBC_HUMAN 0.034500249 375.2_611.3 LDFHFSSDR_INHBC_HUMAN 0.035166664 375.2_464.2 GAVHVVVAETDYQS CO8G_HUMAN0.037334975 FAVLYLER_ 822.8_580.3 HELTDEELQSLFTN AFAM_HUMAN 0.039258528FANVVDK_ 817.1_854_4 AYSDLSR_ SAMP_HUMAN 0.04036485 406.2_375.2 YYLQGAK_ITIH4_HUMAN 0.042204165 421.7_516.3 ILPSVPK_ PGH1_HUMAN 0.042397885377.2_264.2 ELLESYIDGR_ THRB_HUMAN 0.043053589 597.8_710.4ALALPPLGLAPLLN SHBG_HUMAN 0.045692283 LWAKPQGR_ 770.5_256.2 VGEYSLYIGR_SAMP_HUMAN 0.04765767 578.8_871.5 ANDQYLTAAALHNL ILIA_HUMAN 0.048928376DEAVK_ 686.4_317.2 YYGYTGAFR_ TRFL_HUMAN 0.049568351 549.3_551.3

TABLE 56 Univariate p-values for Adjusted Peak Areas in Time to BirthLinear Model Protein pvalue ADA12_HUMAN 0.003412707 ENPP2_HUMAN0.003767393 ADA12_HUMAN 0.004194234 ENPP2_HUMAN 0.004298493 ADA12_HUMAN0.004627197 ADA12_HUMAN 0.004918852 ENPP2_HUMAN 0.005792374 CO6_HUMAN0.005858282 ENPP2_HUMAN 0.007123606 CO6_HUMAN 0.007162317 ENPP2_HUMAN0.008228726 ENPP2_HUMAN 0.009168492 PSG9_HUMAN 0.011531192 PSG9_HUMAN0.019389627 PSG9_HUMAN 0.023680865 INHBE_HUMAN 0.02581564 B2MG_HUMAN0.026544689 LBP_HUMAN 0.031068274 PSG9_HUMAN 0.031091843 APOA2_HUMAN0.033130498 INHBC_HUMAN 0.03395215 CBG_HUMAN 0.034710348 PSGx_HUMAN0.035719227 CBG_HUMAN 0.036331871 CSH_HUMAN 0.039896611 CSH_HUMAN0.04244001 SAMP_HUMAN 0.047112128 LBP_HUMAN 0.048141371 LBP_HUMAN0.048433174 CO6_HUMAN 0.04850949 PSGx_HUMAN 0.049640167

TABLE 57 Univariate p-values for Ad_usted Peak Areas in Gestation Age at Birth Linear Model Transition Protein pvalueENPAVIDFELAPIVDLVR_ CO6_HUMAN 0.000117239 670.7_811.5ENPAVIDFELAPIVDLVR_ CO6_HUMAN 0.000130113 670.7_601.4 TYLHTYESEI_ENPP2_HUMAN 0.000160472 628.3_908.4 TYLHTYESEI_ ENPP2_HUMAN 0.000175167628.3_515.3 TEFLSNYLTNVDDITLV ENPP2_HUMAN 0.000219886 PGTLGR_846.8_600.3 TEFLSNYLTNVDDITLV ENPP2_HUMAN 0.000328416 PGTLGR_846.8_699.4 WWGGQPLWITATK_ ENPP2_HUMAN 0.000354644 772.4_373.2WWGGQPLWITATK_ ENPP2_HUMAN 0.000390821 772.4_929.5 SEYGAALAWEK_CO6_HUMAN 0.000511882 612_8_788.4 LDFHFSSDR_ INHBC_HUMAN 0.000600637375.2_448.2 ALVLELAK_ INHBE_HUMAN 0.000732445 428.8_672.4GLQYAAQEGLLALQSE LBP_HUMAN 0.000743924 LLR_ 1037_1_929_5DVLLLVHNLPQNLPGY PSG9_HUMAN 0.000759173 FWYK_ 810.4_960.5 FGFGGSTDSGPIR_ADA12_HUMAN 0.001224347 649.3_745.4 DVLLLVHNLPQNLPGY PSG9_HUMAN0.001241526 FWYK_ 810.4_328.2 GYVIIKPLVWV_ SAMP_HUMAN 0.001853785643.9_304.2 SPELQAEAK_ APOA2_HUMAN 0.001856303 486.8_659.4GLQYAAQEGLLALQSE LBP_HUMAN 0.001978165 LLR_ 1037.1_858_5 LDFHFSSDR_INHBC_HUMAN 0.002098948 375.2_61_F3 LIEIANHVDK_ ADA12_HUMAN 0.002212096384.6_683.4 SFRPFVPR_ LBP_HUMAN 0.002545286 335.9_272.2 SFRPFVPR_LBP_HUMAN 0.002620268 335.9_635.3 WSAGLTSSQVDLYIPK_ CBG_HUMAN0.002787272 883.0_515_3 DLHLSDVFLK_ CO6_HUMAN 0.002954612 396.2_260.2LIEIANHVDK_ ADA12_HUMAN 0.002955081 384.6_498.3 DVLLLVHNLPQNLPGPSG9_HUMAN 0.003541011 YFWYK_ 810.4_215.1 LFIPQITR_ PSG9_HUMAN0.003750666 494.3_614.4 FGFGGSTDSGPIR_ ADA12_HUMAN 0.003773696649.3_946.5 YYLQGAK_ ITIH4_HUMAN 0.004064026 421.7_516.3 SEYGAALAWEK_CO6_HUMAN 0.004208136 612.8_845.5 AITPPHPASQANIIF FBLN1_HUMAN0.004709104 DITEGNLR_ 825.8_459.3 LDFHFSSDR_ INHBC_HUMAN 0.005355741375.2_464.2 HELTDEELQSLFTNFA AFAM_HUMAN 0.005370567 NVVDK_ 817.1_854.4ALNHLPLEYNSALYSR_ CO6_HUMAN 0.005705922 621.0_696.4 ITQDAQLK_ CBG_HUMAN0.006762484 458.8_702.4 ITLPDFTGDLR_ LBP_HUMAN 0.006993268 624.3_920.5SILFLGK_ THBG_HUMAN 0.007134146 389.2_577.4 WSAGLTSSQVDLYIPK_ CBG_HUMAN0.007670388 883.0_357.2 GVTSVSQIFHSPDLAIR_ IC1_HUMAN 0.007742729609.7_472.3 VGEYSLYIGR_ SAMP_HUMAN 0.007778691 578.8_871.5 ITLPDFTGDLR_LBP_HUMAN 0.008179918 624_3_288_2 YYLQGAK_ ITIH4_HUMAN 0.008404686421.7_327.1 ALNHLPLEYNSALYSR_ CO6_HUMAN 0.008601162 621.0_538_3 DYWSTVK_APOC3_HUMAN 0.008626786 449.7_620.3 TVQAVLTVPK_ PEDF_HUMAN 0.008907523528.3_855.5 ITGFLKPGK_ LBP_HUMAN 0.009155417 320.9_301.2 LFIPQITR_PSG9_HUMAN 0.009571006 494.3_727.4 SPELQAEAK_ APOA2_HUMAN 0.009776508486.8_788.4 DYWSTVK_ APOC3_HUMAN 0.00998356 449.7_347.2 ITGFLKPGK_LBP_HUMAN 0.010050264 320.9_429.3 FLNWIK_ HABP2_HUMAN 0.010372454410.7_560.3 DLHLSDVFLK_ CO6_HUMAN 0.010806378 396.2_366.2GVTSVSQIFHSPDLAIR_ IC1_HUMAN 0.011035991 609.7_908.5 VEHSDLSFSK_B2MG_HUMAN 0.011113172 383.5_468.2 LLDSLPSDTR_ IC1_HUMAN 0.011589013558.8_276.2 LLDSLPSDTR_ IC1_HUMAN 0.011629438 558.8_890.4 QALEEFQK_CO8B_HUMAN 0.011693839 496.8_551.3 LLDSLPSDTR_ IC1_HUMAN 0.012159314558.8_575.3 IIGGSDADIK_ C1S_HUMAN 0.013080243 494.8_762.4 AFIQLWAFDAVK_AMBP_HUMAN 0.013462234 704.9_650.4 GFQALGDAADIR_ TIMP1_HUMAN 0.014370997617.3_717_4 LPNNVLQEK_ AFAM_HUMAN 0.014424891 527.8_730.4 DTDTGALLFIGK_PEDF_HUMAN 0.014967952 625_8_217.1 VQTAHFK_ CO8A_HUMAN 0.01524844277.5_502.3 ILILPSVTR_ PSG1_HUMAN 0.015263132 506.3_559.3 SILFLGK_THBG_HUMAN 0.015265233 389.2_201.1 TVQAVLTVPK_ PEDF_HUMAN 0.015344052528.3_428.3 VEPLYELVTATDFAYSSTVR_ CO8B_HUMAN 0.015451068 754.4_712.4FSLVSGWGQLLDR_ FA7_HUMAN 0.015510454 493.3_447_3 GWVTDGFSSLK_APOC3_HUMAN 0.01610797 598.8_854.4 LSETNR_ PSG1_HUMAN 0.016433362360.2_519.3 TQILEWAAER_ EGLN_HUMAN 0.01644844 608.8_632.3SETEIHQGFQHLHQLFAK_ CBG_HUMAN 0.016720367 717_4_318.1 TNLESILSYPK_IC1_HUMAN 0.017314185 632.8_936.5 TNLESILSYPK_ IC1_HUMAN 0.017593786632.8_807.5 AYSDLSR_ SAMP_HUMAN 0.018531348 406.2_375.2 YEVQGEVFTKPQLWP_CRP_HUMAN 0.019111323 911_0_392.2 AYSDLSR_ SAMP_HUMAN 0.019271266406.2_577.3 QALEEFQK_ CO8B_HUMAN 0.019429489 496.8_680.3 APLTKPLK_CRP_HUMAN 0.020110081 289.9_398.8 FQPTLLTLPR_ IC1_HUMAN 0.020114306593.4_276.1 ITQDAQLK_ CBG_HUMAN 0.020401782 453.8_803.4 AVLH1GEK_THBG_HUMAN 0.02056597 289.5_292.2 ANDQYLTAAALHNLDE ILIA_HUMAN0.020770124 AVK_ 686.4_317.2 VGEYSLYIGR_ SAMP_HUMAN 0.021126414578.8_708.4 TLYSSSPR_ IC1_HUMAN 0.021306106 455.7_533.3 VEHSDLSFSK_B2MG_HUMAN 0.021640643 383.5_234.1 HELTDEELQSLFTNFA AFAM_HUMAN0.021921609 NVVDK_ 817.1_906.5 TLYSSSPR_ IC1_HUMAN 0.022196181455.7_696.3 GYVIIKPLVWV_ SAMP_HUMAN 0.023126336 643.9_854.6DEIPHNDIALLK_ HABP2_HUMAN 0.023232158 459.9_260.2 ILILPSVTR_ PSGx_HUMAN0.023519909 506.3_785.5 WNFAYWAAHQPWSR_ PRG2_HUMAN 0.023697087607.3_545.3 FQPTLLTLPR_ IC1_HUMAN 0.023751959 593.4_712.5AQPVQVAEGSEPDGF GELS_HUMAN 0.024262721 WEALGGK_ 758.0_623.4DEIPHNDIALLK_ HABP2_HUMAN 0.024414348 459.9_510.8 GDSGGAFAVQDPNDK_C1S_HUMAN 0.025075028 739.3_716.3 FLNWIK_ HABP2_HUMAN 0.025649617410.7_561.3 APLTKPLK_ CRP_HUMAN 0.025961162 289.9_357.2 ALDLSLK_ITIH3_HUMAN 0.026233504 380.2_185.1 GWVTDGFSSLK_ APOC3_HUMAN 0.026291884598_8_953.5 SETEIHQGFQHLHQLFAK_ CBG_HUMAN 0.026457136 717.4_447.2GDSGGAFAVQDPNDK_ C1S_HUMAN 0.02727457 739.3_473.2 YEVQGEVFTKPQLWP_CRP_HUMAN 0.028244448 911.0_293.1 HVVQLR_ IL6RA_HUMAN 0.028428028376.2_614.4 DTDTGALLFIGK_ PEDF_HUMAN 0.028773557 625.8_818.5EVPLSALTN1LSAQLI PAI1_HUMAN 0.029150774 SHWK_ 740.8_996.6 AFTECCVVASQLR_CO5_HUMAN 0.029993325 770.9_574.3 TLAFVR_ FA7_HUMAN 0.030064307353.7_492.3 LWAYLTIQELLAK_ ITIH1_HUMAN 0.030368674 781.5_300.2DEIPHNDIALLK_ HABP2_HUMAN 0.031972082 459_9_245_1 AGLLRPDYALLGHR_PGRP2_HUMAN 0.032057409 518.0_369.2 AVYEAVLR_ PEPD_HUMAN 0.032527521460.8_587.4 LPNNVLQEK_ AFAM_HUMAN 0.033807082 527.8_844.5GAVHVVVAETDYQSFA CO8G_HUMAN 0.054370139 VLYLER_ 822_8_580.3WNFAYWAAHQPWSR_ PRG2_HUMAN 0.0349737 607.3_673.3 EAQLPVIENK_ PLMN_HUMAN0.035304322 570.8_329.2 VQEAHLTEDQIFYFPK_ CO8G_HUMAN 0.035704382655.7_701.4 AFIQLWAFDAVK_ AMBP_HUMAN 0.035914532 704.9_836.4 SGFSFGFK_CO8B_HUMAN 0.037168221 438.7_585.3 SGFSFGFK_ CO8B_HUMAN 0.040182596438.7_732.4 DADPDTFFAK_ AFAM_HUMAN 0.041439744 563.8_302.1 EAQLPV1ENK_PLMN_HUMAN 0.041447675 570.8_699.4 IIGGSDADIK_ C1S_HUMAN 0.041683256494.8_260.2 AVLT1DEK_ A1AT_HUMAN 0.043221658 444.8_718.4 SEPRPGVLLR_FA7_HUMAN 0.044079127 375.2_654.4 YHFEALADTGISSEFY CO8A_HUMAN0.045313634 DNANDLLSK_ 940.8_874.5 HFQNLGK_ AFAM_HUMAN 0.047118971422.2_527.2 LEQGENVFLQATDK_ C1QB_HUMAN 0.047818928 796.4_822.4NTVISVNPSTK_ VCAM1_HUMAN 0.048102262 580.3_732.4 YYGYTGAFR_ TRFL_HUMAN0.048331316 549.3_551.3 ISLLLIESWLEPVR_ CSH_HUMAN 0.049561581834.5_500.3 LQVLGK_ A2GL_HUMAN 0.049738493 329.2_416.3

TABLE 58 Univariate p-values for Peak Area Ratios (<37 vs >37 weeks)UniProt_ID Transition pvalue SHBG_HUMAN IALGGLLFPASN 0.006134652 LR_481.3_ 657.4 SHBG_HUMAN IALGGLLFPASN 0.019049498 LR_ 481.3_ 412.3APOC3_HUMAN DALSSVQESQVAQ 0.020688543 QAR_ 573.0_ 672.4 THBG_HUMANAVLH1GEK_ 0.0291698 289.5_ 292.2 PSG9_HUMAN DVLLLVHNLPQNL 0.033518454PGYFWYK_ 810.4_ 960.5 APOC3_HUMAN DALSSVQESQVAQ 0.043103265 QAR_ 573.0_502.3 PSG9_HUMAN LFIPQITR_ 0.04655948 494.3_ 614.4

TABLE 59 Univariate p-values for Peak Area Ratios (<37 vs >40 weeks)UniProt_ID Transition pvalue APOC3_ DALSSVQESQVA 0.011174438 HUMANQQAR_573.0_ 672.4 APOC3_ DALSSVQESQVA 0.015231617 HUMAN QQAR_573.0_502.3 PSG9_ LFIPQITR_ 0.018308413 HUMAN 494.3_614.4 PSG9_ LFIPQITR_0.027616871 HUMAN 494.3_727.4 PSG9_ DVLLLVHNLPQN 0.028117582 HUMANLPGYFWYK_ 810.4_960.5 THBG_ AVLHIGEK_ 0.038899107 HUMAN 289.5_292.2 CO6_ALNHLPLEYNSA 0.040662269 HUMAN LYSR_621.0_ 696.4 ENPP2_ TYLHTYESEI_0.044545826 HUMAN 628.3_908.4

TABLE 60 Univariate p-values for Peak Area Ratios inTime to Birth Linear Model UniProt_ID Transition pvalue ADA12_FGFGGSTDSGPIR_ 5.85E−27 HUMAN 649.3_946.5 ADA12_ FGFGGSTDSGPIR_ 2.65E−24HUMAN 649.3_745.4 PSG4_ TLF1FGVTK_ 1.07E−20 HUMAN 513.3_215.1 PSG4_TLFIFGVTK_ 2.32E−20 HUMAN 513.3_811.5 PSGx_ ILILPSVTR_ 8.25E−16 HUMAN506.3_785.5 PSGx_ ILILPSVTR_ 9.72E−16 HUMAN 506.3_559.3 PSG1_ FQLPGQK_1.29E−12 HUMAN 409.2_429.2 PSG11_ LFIPQITPK_ 2.11E−12 HUMAN 528.8_261.2PSG1_ FQLPGQK_ 2.33E−12 HUMAN 409.2_276.1 PSG11_ LFIPQITPK_ 3.90E−12HUMAN 528.8_683_4 PSG6_ SNPVTLNVLY 5.71E−12 HUMAN GPDLPR_ 585.7_817.4PSG6_ SNPVTLNVLY 1.82E−11 HUMAN GPDLPR_ 585.7_654.4 VGFR3_ SGVDLADSNQK_4.57E−11 HUMAN 567.3_662.3 INHBE_ ALVLELAK_ 1.04E−08 HUMAN 428.8_331.2PSG2_ IHPSYTNYR_ 6.27E−08 HUMAN 384.2_452.2 PSG9_ LFIPQITR_ 1.50E−07HUMAN 494.3_727.4 VGFR3_ SGVDLADSNQK_ 2.09E−07 HUMAN 567.3_591.3 PSG9_LFIPQITR_ 2.71E−07 HUMAN 494.3_614_4 PSG9_ DVLLLVHNLPQ 3.10E−07 HUMANNLPGYFWYK_ 810.4_960.5 PSG2_ IHPSYTNYR_ 2.55E−06 HUMAN 384.2_338.2ITIH3_ LIQDAVTGLTV 2.76E−06 HUMAN NGQITGDK_ 972.0_640.4 ENPP2_TYLHTYESEI_ 2.82E−06 HUMAN 628.3_908_4 ENPP2_ WWGGQPLWI 3.75E−06 HUMANTATK_ 772.4_373.2 PSG9_ DVLLLVHNLPQ 3.94E−06 HUMAN NLPGYFWYK_810.4_328.2 B2MG_ VEHSDLSFSK_ 5.42E−06 HUMAN 383.5_468.2 ENPP2_ WWGGQPLW7.93E−06 HUMAN ITATK_ 772.4_929.5 ANGT_ ALQDQLV 1.04E−05 HUMAN LVAAK_634.9_289.2 B2MG_ VNHVTLSQPK_ 1.46E−05 HUMAN 374.9_244.2 AFAM_LPNNVLQEK_ 1.50E−05 HUMAN 527.8_730.4 AFAM_ LPNNVLQEK_ 1.98E−05 HUMAN527.8_844.5 THBG_ AVLHIGEK_ 2.15E−05 HUMAN 289.5_292.2 ENPP2_TYLHTYESEI_ 2.17E−05 HUMAN 628.3_515.3 IL12B_ DIIKPDPPK_ 3.31E−05 HUMAN511.8_342.2 AFAM_ DADPDTFFAK_ 6.16E−05 HUMAN 563.8_302.1 THBG_ AVLHIGEK_8.34E−05 HUMAN 289.5_348.7 PSG9_ DVLLLVHNLPQ 0.000104442 HUMANNLPGYFWYK_ 810.4_215.1 B2MG_ VEHSDLSFSK_ 0.000140786 HUMAN 383.5_234.1TRFL_ YYGYTGAFR_ 0.000156543 HUMAN 549.3_450.3 HEMO_ QGHNSVFLIK_0.000164578 HUMAN 381.6_260.2 A1BG_ LLELTGPK_ 0.000171113 HUMAN435.8_227.2 CO6_ ALNHLPLEYN 0.000242116 HUMAN SALYSR_ 621.0_696.4 CO6_ALNHLPLEYN 0.00024681 HUMAN SALYSR_ 621.0_538.3 ALS_ IRPHTFTGLSGLR_0.000314359 HUMAN 485.6_432.3 IT1H2_ LSNHNHGlAQR_ 0.0004877 HUMAN413.5_544_3 PEDF_ TVQAVLTVPK_ 0.000508174 HUMAN 528.3_855.5 AFAM_HFQNLGK_ 0.000522139 HUMAN 422.2_527.2 FLNA_ TGVAVNKPAEFT 0.000594403HUMAN VDAK_ 549.6_258.1 ANGT_ ALQDQLVLVAAK_ 0.000640673 HUMAN634.9_956.6 AFAM_ HFQNLGK_ 0.000718763 HUMAN 422.2_285.1 HGFA_LHKPGVYTR_ 0.000753293 HUMAN 357.5_692.4 HGFA_ LHKPGVYTR_ 0.000909298HUMAN 357.5_479.3 HABP2_ FLNWIK_ 0.001282014 HUMAN 410.7_561.3 FETUA_HTLNQIDEVK_ 0.001389792 HUMAN 598.8_951.5 AFAM_ DADPDIFFAK_ 0.001498237HUMAN 563.8_825.4 B2MG_ VNHVTLSQPK_ 0.001559862 HUMAN 374.9_459.3 ALS_IRPHTFTGLSGLR_ 0.001612361 HUMAN 485.6_545.3 A1BG_ LLELTGPK_ 0.002012656HUMAN 435.8_644.4 F13B_ LIENGYFHPVK_ 0.00275216 HUMAN 439.6_343.2 ITIH2_LSNENHGIAQR_ 0.00356561 HUMAN 413.5_519.8 APOC3_ DALSSVQESQVA 0.00392745HUMAN QQAR_573.0_ 672.4 F13B_ LIENGYFHPVK_ 0.00434836 HUMAN 439.6_627.4PEDF_ TVQAVLTVPK_ 0.00482765 HUMAN 528.3_428.3 PLMN_ YEFLNGR_0.007325436 HUMAN 449.7_293.1 HEMO_ QGHNSVFLIK_ 0.009508516 HUMAN381.6_520.4 FETUA_ HTLNQIDEVK_ 0.010018936 HUMAN 598.8_958.5 CO5_LQGTLPVEAR_ 0.011140661 HUMAN 542.3_842.5 PLMN_ YEFLNGR_ 0.01135322HUMAN 449.7_606.3 CO5_ TLLPVSKPE1R_ 0.015045275 HUMAN 418.3_288.2 HABP2_FLNWIK_ 0.01523134 HUMAN 410.7_560.3 APOC3_ DALSSVQESQVA 0.01584708HUMAN QQAR_573.0_ 502.3 CO5_ LQGTLPVEAR_ 0.017298064 HUMAN 542.3_571.3CFAB_ DISEWTPR_ 0.021743221 HUMAN 508.3_472.3 CERU_ TTIEKPVWLG0.02376225 FLGPIIK_ HUMAN 638.0_640.4 CO8G_ SLPVSDSVLSGFEQR_ 0.041150397HUMAN 810.9_723.3 CO8G_ FLQEQGHR_ 0.042038143 HUMAN 338.8_497.3 CO5_VFQFLEK_ 0.043651929 HUMAN 455.8_811.4 CO8B_ QALEEFQK_ 0.04761631 HUMAN496.8_680.3

TABLE 61 Univariate p-values for Peak Area Ratiosin Gestation Age at Birth Linear Model UniProt_ID Transition pvaluePSG9_ DVLLLVHNLPQNLP 0.000431547 HUMAN GYFWYK_ 810.4_960.5 B2MG_VEHSDLSFSK_ 0.000561148 HUMAN 383.5_468.2 PSG9_ DVLLLVHNLPQNLP0.000957509 HUMAN GYFWYK_ 810.4_328.2 ENPP2_ TYLHTYESEI_ 0.001058809HUMAN 628.3_908.4 THBG_ AVLHIGEK_ 0.001180484 HUMAN 289.5_292.2 ENPP2_WWGGQPLWITATK_ 0.001524983 HUMAN 772.4_373.2 PSG9_ LFIPQITR_ 0.001542932HUMAN 494.3_614_4 ENPP2_ WWGGQPLWITATK_ 0.002047607 HUMAN 772.4_929.5ENPP2_ TYLHTYESEI_ 0.003087492 HUMAN 628.3_515.3 PSG9_ LFIPQITR_0.00477154 HUMAN 494.3_727.4 PSG9_ DVLLLVHNLPQ 0.004824351 HUMANNLPGYFWYK_ 810.4_215.1 THBG_ AVLHIGEK_ 0.006668084 HUMAN 289.5_348.7AFAM_ LPNNVLQEK_ 0.006877647 HUMAN 527.8_730.4 ADA12_ FGFGGSTDSGPIR_0.011738104 HUMAN 649.3_745_4 PEDF_ TVQAVLTVPK_ 0.013349511 HUMAN528.3_855.5 A1BG_ LLELTGPK_ 0.015793885 HUMAN 435.8_227.2 ITIH3_ALDLSLK_ 0.016080436 HUMAN 380.2_185.1 ADA12_ FGFGGSTDSGP 0.017037089HUMAN IR_ 649.3_946.5 B2MG_ VEHSDLSFSK_ 0.017072093 HUMAN 383.5_234.1CO6_ ALNHLPLEYNS 0.024592775 HUMAN ALYSR_ 621.0_696.4 TRFL_ YYGYTGAFR_0.030890831 HUMAN 549.3_450.3 AFAM_ DADPDTFFAK_ 0.033791429 HUMAN563.8_302.1 CO6_ ALNHLPLEYNS 0.034865341 HUMAN ALYSR_ 621.0_538.3 AFAM_LPNNVLQEK_ 0.039880594 HUMAN 527.8_844.5 PEDF_ TVQAVLTVPK_ 0.040854402HUMAN 528.3_428.3 PLMN_ EAQLPVIENK_ 0.041023812 HUMAN 570.8_329.2 LBP_ITLPDFTGDLR_ 0.042276813 HUMAN 624.3_920.5 CO8G_ VQEAHLTEDQI 0.042353851HUMAN FYFPK_ 655.7_701.4 PLMN_ YEFLNGR_ 0.04416504 HUMAN 449.7_606.3B2MG_ VNHVTLSQPK_ 0.045458409 HUMAN 374.9_459.3 CFAB_ DISEVVTPR_0.046493405 HUMAN 508.3_472.3 INHBE_ ALVLELAK_ 0.04789353 HUMAN428.8_331.2

TABLE 62 Random Forest Importance Values Using Adjusted Peak AreasTransition Rank Importance INHBE_ALVLELAK_428.8_672.4 1 2964.951571EGLN_TQILEWAAER_608.8_761.4 2 1218.3406 FA7_SEPRPGVLLR_375.2_654.4 3998.92897 CBG_ITQDAQLK_458.8_702.4 4 930.9931102ITIH3_ALDLSLK_380.2_185.1 5 869.6315408 ENPP2_WWGGQPLWITATK_772.4_929.56 768.9182114 CBG_ITQDAQLK_458.8_803.4 7 767.8940452PSG1_LSETNR_360.2_519.3 8 714.6160065CAA60698_LEPLYSASGPGLRPLVIK_637.4_834.5 9 713.4086612INHBC_LDFHFSSDR_375.2_611.3 11 681.2442909 CBG_QINSYVK_426.2_610.3 12674.3363415 LBP_GLQYAAQEGLLALQSELLR_1037.1_858.5 13 603.197751A1BG_LLELTGPK_435.8_644.4 14 600.9902818 CO6_DLHLSDVFLK_396.2_366.2 15598.8214342 VCAM1_TQIDSPLSGK_523.3_816.5 16 597.4038769LRP1_NAVVQGLEQPHGLVVHPLR_688.4_285.2 17 532.0500081CBG_QINSYVK_426.2_496.3 18 516.5575201CO6_ENPAVIDFELAP1VDLVR_670.7_811.5 19 501.4669261ADA12_FGFGGSTDSGPIR_649.3_745.4 20 473.5510333CO6_DLHLSDVFLK_396.2_260.2 21 470.5473702 ENPP2_TYLHTYESEI_628.3_908.422 444.7580726 A1BG_LLELTGPK_435.8_227.2 23 444.696292FRIH_QNYHQDSEAAINR_515.9_544.3 24 439.2648872ENPP2_TEFLSNYLTNVDDITLVPGTLGR_846_8_600.3 25 389.3769604CBG_WSAGLTSSQVDLYIPK_883.0_515.3 26 374.0749768C1QC_FQSVFTVTR_542.8_623.4 27 370.6957977GELS_DPDQTDGLGLSYLSSHIANVER_796.4_456.2 28 353.1176588A1BG_ATWSGAVLAGR_544.8_643.4 29 337.4580124 APOA1_AKPALEDLR_506.8_813.530 333.5742035 ENPP2_TYLHTYESEI_628.3_515.3 31 322.6339162PEPD_AVYEAVLR_460.8_750.4 32 321.4377907 TIMP1_GFQALGDAADIR_617.3_717.433 310.0997949 ADA12_LIEIANHVDK_384.6_498.3 34 305.8803542PGRP2_WGAAPYR_410.7_577.3 35 303.5539874 PSG9_LFIPQITR_494.3_614.4 36300.7877317 HABP2_FLNWIK_410.7_560.3 37 298.3363186CBG_WSAGLTSSQVDLYIPK_883.0_357.2 38 297.2474385PSG2_IHPSYTNYR_384.2_452.2 39 292.6203405 PSG5_LSIPQITTK_500.8_800.5 40290.2023364 HABP2_FLNWIK_410.7_561.3 41 289.5092933CO6_SEYGAALAWEK_612.8_788.4 42 287.7634114 ADA12_LIEIANHVDK_384.6_683.443 286.5047372 EGLN_TQILEWAAER_608.8_632.3 44 284.5138846CO6_ENPAVIDFELAPIVDLVR_670.7_601.4 45 273.5146272FA7_FSLVSGWGQLLDR_493.3_447.3 46 271.7850098 ITIH3_ALDLSLK_380.2_575.347 269.9425709 ADA12_FGFGGSTDSGPIR_649.3_946.5 48 264.5698225FETUA_AALAAFNAQNNGSNFQLEEISR_789.1_746.4 49 247.4728828FBLN1_AITPPHPASQANIIFDITEGNLR_825.8_459.3 50 246.572102TSP1_FVFGTTPEDILR_697.9_843.5 51 245.0459575VCAM1_NTVISVNPSTK_580.3_732.4 52 240.576729ENPP2_TEFLSNYLTNVDDITLVPGTLGR_846.8_699.4 53 240.1949512FBLN3_ELPQSIVYK_538.8_409.2 55 233.6825304ACTB_VAPEEHPVLLTEAPLNPK_652.0_892.5 56 226.9772749TSP1_FVFGTTPEDILR_697.9_742.4 57 224.4627393 PLMN_EAQLPVIENK_570.8_699.458 221.4663735 C1S_IIGGSDADEK_494.8_260.2 59 218.069476ILIA_ANDQYLTAAALHNLDEAVK_686.4_317.2 60 216.5531949PGRP2_WGAAPYR_410.7_634.3 61 211.0918302 PSG5_LSIPQITTK_500.8_687.4 62208.7871461 PSG6_SNPVTLNVLYGPDLPR_585.7_654.4 63 207.9294937PRG2_WNFAYWAAHQPWSR_607.3_545.3 64 202.9494031CXCL2_CQCLQTLQGIHLK_13p8RT_533.6_567.4 65 202.9051326CXCL2_CQCLQTLQGIHLK_13p48RT_533.6_695.4 66 202.6561548G6PE_LLDFEFSSGR_585.8_553.3 67 201.004611 GELS_TASDFITK_441.7_710.4 68200.2704809 B2MG_VEHSDLSFSK_383.5_468.2 69 199.880987CO8B_IPGIFELGISSQSDR_809.9_849.4 70 198.7563875PSG8_LQLSETNR_480.8_606.3 71 197.6739966LBP_GLQYAAQEGLLALQSELLR_1037.1_929.5 72 197.4094851AFAM_LPNNVLQEK_527.8_844.5 73 196.8123228 MAGE 74 196.2410502PSG2_IHPSYTNYR_384.2_338.2 75 196.2410458 PSG9_LFIPQITR_494.3_727.4 76193.5329266 TFR1_YNSQLLSFVR_613.8_734.5 77 193.2711994C1R_QRPPDLDTSSNAVDLLFFTDESGDSR_961.5_866.3 78 193.0625419PGH1_ILPSVPK_377.2_264.2 79 190.0504508 FA7_SEPRPGVLLR_375.2_454.3 80188.2718422 FA7_TLAFVR_353.7_274.2 81 187.6895294PGRP2_DGSPDVTTADIGANTPDATK_973.5_844.4 82 185.6017519C1S_IIGGSDADIK_494.8_762.4 83 184.5985543 PEPD_VPLALFALNR_557.3_620.4 84184.3962957 C1S_EDTPNSVWEPAK_686.8_630.3 85 179.2043504CHL1_TAVTANLDIR_537.3_802.4 86 174.9866792 CHL1_VIAVNEVGR_478.8_744.4 88172.2053147 SDF1_ILNTPNCALQIVAR_791.9_341.2 89 171.4604557PAI1_EVPLSALTNILSAQLISHWK_740.8_996.6 90 169.5635635AMBP_AFIQLWAFDAVK_704.9_650.4 91 169.2124477 G6PE_LLDFEFSSGR_585.8_944.492 168.2398598 THBG_SILFLGK_389.2_577.4 93 166.3110206PRDX2_GLFIIDGK_431.8_545.3 94 164.3125132ENPP2_WWGGQPLWITATK_772.4_373.2 95 163.4011689VGFR3_SGVDLADSNQK_567.3_662.3 96 162.8822352C1S_EDTPNSVWEPAK_686.8_315.2 97 161.6140915 AFAM_DADPDTFFAK_563.8_302.198 159.5917449 CBG_SETEIHQGFQHLHQLFAK_717.4_447.2 99 156.1357404C1S_LLEVPEGR_456.8_686.4 100 155.1763293 PTGDS_GPGEDFR_389.2_623.3 101154.9205208 ITIH2_IYLQPGR_423.7_329.2 102 154.6552717FA7_TLAFVR_353.7_492.3 103 152.5009422 FA7_FSLVSGWGQLLDR_493.3_403.2 104151.9971204 SAMP_VGEYSLYIGR_578.8_871.5 105 151.4738449APOH_EHSSLAFWK_552.8_267.1 106 151.0052645PGRP2_AGLLRPDYALLGHR_518.0_595.4 107 150.4149907C1QC_FNAVLTNPQGDYDTSTGK_964.5_333.2 108 149.2592827PGRP2_AGLLRPDYALLGHR_518.0_369.2 109 147.3609354PGRP2_TFTLLDPK_467.8_686.4 111 145.2145223 CO5_TDAPDLPEENQAR_728.3_843.4112 144.5213118 THRB_ELLESYIDGR_597.8_839.4 113 143.924639GELS_DPDQTDGLGLSYLSSHIANVER_796.4_328.1 114 142.8936101TRFL_YYGYTGAFR_549.3_450.3 115 142.8651352 HEMO_QGHNSVFLIK_381.6_260.2116 142.703845 C1S_GDSGGAFAVQDPNDK_739.3_716.3 117 142.2799122B1A4H9_AHQLAIDTYQEFR_531.3_450.3 118 138.196407C1S_SSNNPHSPIVEEFQVPYNK_729.4_261.2 119 136.7868935HYOU1_LPATEKPVLLSK_432.6_347.2 120 136.1146437 FETA_GYQELLEK_490.3_502.3121 135.2890322 LRP1_SERPPIFEIR_415.2_288.2 122 134.6569527CO6_SEYGAALAWEK_612.8_845.5 124 132.8634704CERU_TTIEKPVWLGFLGPIIK_638.0_844.5 125 132.1047746IBP1_AQETSGEEISK_589.8_850.4 126 130.934446SHBG_VVLSSGSGPGLDLPLVLGLPLQLK_791.5_768.5 127 128.2052287CBG_SETEIHQGFQHLHQLFAK_717.4_318.1 128 127.9873837A1AT_LSITGTYDLK_555.8_696.4 129 127.658818PGRP2_DGSPDVTTADIGANTPDATK_973.5_531.3 130 126.5775806C1QB_LEQGENVFLQATDK_796.4_675.4 131 126.1762726EGLN_GPITSAAELNDPQSILLR_632.4_826.5 132 125.7658253IL12B_YENYTSSFFIR_713.8_293.1 133 125.0476631B2MG_VEHSDLSFSK_383.5_234.1 134 124.9154706PGH1_AEHPTWGDEQLFQTTR_639.3_765.4 135 124.8913193INHBE_ALVLELAK_428.8_331.2 136 124.0109276HYOU1_LPATEKPVLLSK_432.6_460.3 137 123.1900369CXCL2_CQCLQTLQGIHLK_13p48RT_533.6_567.4 138 122.8800873PZP_AVGYLITGYQR_620.8_523.3 139 122.4733204AFAM_IAPQLSTEELVSLGEK_857.5_333.2 140 122.4707849ICAM1_VELAPLPSWQPVGK_760.9_400.3 141 121.5494206CHL1_VIAVNEVGR_478.8_284.2 142 119.0877137APOB_ITENDIQIALDDAK_779.9_632.3 143 118.0222045 SAMP_AYSDLSR_406.2_577.3144 116.409429 AMBP_AFIQLWAFDAVK_704.9_836.4 145 116.1900846EGLN_GPITSAAELNDPQSILLR_632.4_601.4 146 115.8438804LRP1_NAVVQGLEQPHGLVVHPLR_688.4_890.6 147 114.539707SHBG_VVLSSGSGPGLDLPLVLGLPLQLK_791.5_598.4 148 113.1931134IBP1_AQETSGEEISK_589.8_979.5 149 112.9902709PSG6_SNPVTLNVLYGPDLPR_585.7_817.4 150 112.7910917APOC3_DYWSTVK_449.7_347.2 151 112.544736 C1R_WILTAAHTLYPK_471.9_621.4152 112.2199708 ANGT_ADSQAQLLLSTVVGVFTAPGLHLK_822.5_983.6 153111.9634671 PSG9_DVLLLVHNLPQNLPGYFWYK_810.4_328.2 154 111.5743214A1AT_AVLTIDEK_444.8_605.3 155 111.216651 PSGx_ILILPSVTR_506.3_785.5 156110.8482935 THRB_ELLESYIDGR_597.8_710.4 157 110.7496103SHBG_ALALPPLGLAPLLNLWAKPQGR_770.5_256.2 158 110.5091269PZP_QTLSWTVTPK_580.8_545.3 159 110.4675104SHBG_ALALPPLGLAPLLNLWAKPQGR_770.5_457.3 160 110.089808PSG4_TLFIFGVTK_513.3_811.5 161 109.9039967 PLMN_YEFLNGR_449.7_293.1 162109.6880397 PEPD_AVYEAVLR_460.8_587.4 163 109.3697285PLMN_LSSPAVITDK_515.8_830.5 164 108.963353FINC_SYTITGLQPGTDYK_772.4_352.2 165 108.452612C1R_WILT_AAHTL_YPK_471.9_407.2 166 107.8348417CHL1_TAVTANLDIR_537.3_288.2 167 107.7278897TENA_AVDIPGLEAATPYR_736.9_286.1 168 107.6166195CRP_YEVQGEVFTKPQLWP_911.0_293.1 169 106.9739589APOB_SVSLPSLDPASAK_636.4_885.5 170 106.5901668 PRDX2_SVDEALR_395.2_488.3171 106.2325046 CO8A_YHFEALADTGISSEFYDNANDLLSK_940.8_301.1 172105.8963287 C1QC_FQSVFTVTR_542.8_722.4 173 105.4338742PSGx_ILILPSVTR_506.3_559.3 174 105.1942655 VCAM1_TQIDSPLSGK_523.3_703.4175 105.0091767 VCAM1_NTVISVNPSTK_580.3_845.5 176 104.8754444CSH_ISLLLIESWLEPVR_834.5_500.3 177 104.6158295HGFA_EALVPLVADHK_397.9_439.8 178 104.3383142CGB1_CRPINATLAVEK_457.9_660.4 179 104.3378072APOB_IEGNLIFDPNNYLPK_874.0_414.2 180 103.9849346C1QB_LEQGENVFLQATDK_796.4_822.4 181 103.9153207APOH_EHSSLAFWK_552.8_838.4 182 103.9052103 CO5_LQGTLPVEAR_542.3_842.5183 103.1061869 SHBG_1ALGGLLFPASNLR_481.3_412.3 184 102.2490294B2MG_VNHVTLSQPK_374.9_459.3 185 102.1204362 APOA2_SPELQAEAK_486.8_659.4186 101.9166647 FLNA_TGVAVNKPAEFTVDAK_549.6_258.1 187 101.5207852PLMN_YEFLNGR_449.7_606.3 188 101.2531011

TABLE 63 Random Forest Importance Values Using Peak Area Ratios VariableRank Importance HABP2_FLNWIK_ 1 3501.905733 410.7_561.3 ADA12_FGFGGST 23136.589992 DSGPIR_ 649.3_946.5 A1BG_ 3 2387.891934 LLELTGPK_435.8_227.2 B2MG_ 4 1431.31771 VEHSDLSFSK_ 383.5_234.1 ADA12_FGFGGST 51400.917331 DSGPIR_ 649.3_745.4 B2MG_ 6 1374.453629 VEHSDLSFSK_383.5_468.2 APOB_ 7 1357.812445 IEGNLIFDPNN YLPK_ 874.0_414.2PSG9_DVLLLVHNL 8 1291.934596 PQNLPGYFWYK_ 810.4_960.5 A1BG_ 91138.712941 LLELTGPK_ 435.8_644.4 ITIH3_ALDLSLK_ 10 1137.127027380.2_185.1 ENPP2_TYLHTYESEI_ 11 1041.036693 628.3_908.4 IL12B_ 12970.1662913 YENYTSSFFIR_ 713.8_293.1 ENPP2_WWGGQPL 13 953.0631062WITATK_ 772.4_373.2 ENPP2_TYLHTYESEI_ 14 927.3512901 628.3_515.3PSG9_LFIPQITR_ 15 813.9965357 494.3_614.4 MAGE 16 742.2425022ENPP2_WWGGQPL 17 731.5206413 WITATK_ 772.4_929.5 CERU_ 18 724.7745695TTIEKPVWLGFL GPIIK_ 638.0_640.4 ITIH3_ALDLSLK_ 19 710.1982467380.2_575.3 PSG2_IHPSYTNYR_ 20 697.4750893 384.2_452.2 ITIH1_LWAYLTI 21644.7416886 QELLAK_ 781.5_371.2 INHBE_ 22 643.008853 ALVLELAK_428.8_331.2 HGFA_ 23 630.8698445 LHKPGVYTR_ 357.5_692.4 TRFL_ 24609.5866675 YYGYTGAFR_ 549.3_450.3 THBG_ 25 573.9320948 AVLHIGEK_289.5_348.7 GELS_ 26 564.3288862 TASDFITK_ 441.7_710.4 PSG9_LFIPQITR_ 27564.1749327 494.3_727.4 VGFR3_SGVDLA 28 563.8087791 DSNQK_ 567.3_662.3INHA_ 29 554.210214 TTSDGGYSFK_ 531.7_860.4 PSG9_DVLLLVHNL 30545.1743627 PQNLPGYFWYK_ 810.4_328.2 HYOU1_LPATEK 31 541.6208032 PVLLSK_432.6_347.2 C08G_ 32 541.3193428 VQEAHLTEDQIFYFPK_ 655.7_701.4 BMI 33540.5028818 HGFA_ 34 536.6051948 LHKPGVYTR_ 357.5_479.3 PSG2_IHPSYTNYR_35 536.5363489 384.2_338.2 GELS_ 36 536.524931 AQPVQVAEGSEPDGFW EALGGK_758.0_623.4 PSG6_SNPVTLNVLYG 37 520.108646 PDLPR_ 585.7_654.4HABP2_FLNWIK_ 38 509.0707814 410.7_560.3 PGH1_ILPSVPK_ 39 503.593718377.2_527.3 HYOU1_LPATEKPVL 40 484.047422 LSK_ 432.6_460.3C06_ALNHLPLEYNSA 41 477.8773179 LYSR_ 621.0_696.4 INHBE_ 42 459.1998276ALVLELAK_ 428.8_672.4 PLMN_ 43 452.9466414 LSSPAVITDK_ 515.8_743.4PSG9_DVLLLVHNLPQ 44 431.8528248 NLPGYFWYK_ 810.4_215.1BGH3_LTLLAPLNSVFK_ 45 424.2540315 658.4_875.5 AFAM_ 46 421.4953221LPNNVLQEK_ 527.8_730.4 ITIH2_LSNENHGIAQR_ 47 413.1231437 413.5_519.8GELS_ 48 404.2679723 TASDFITK_ 441.7_781.4 FETUA_ 49 400.4711207 AHYDLR_387.7_566.3 CERU_ 50 396.2873451 TTIEKPVWLGFLGPI1K_ 638.0_844.5PSGx_ILILPSVTR_ 51 374.5672526 506.3_785.5 APOB_ 52 371.1416438SVSLPSLDPASAK_ 636.4_885.5 FLNA_ 53 370.4175588 TGVAVNKPAEFTVDAK_549.6_258.1 PLMN_ 54 367.2768078 YEFLNGR_ 449.7_606.3 PSGx_ILILPSVTR_ 55365.7704321 506.3_559.3

From the foregoing description, it will be apparent that variations andmodifications can be made to the invention described herein to adopt itto various usages and conditions. Such embodiments are also within thescope of the following claims.

The recitation of a listing of elements in any definition of a variableherein includes definitions of that variable as any single element orcombination (or subcombination) of listed elements. The recitation of anembodiment herein includes that embodiment as any single embodiment orin combination with any other embodiments or portions thereof.

All patents and publications mentioned in this specification are hereinincorporated by reference to the same extent as if each independentpatent and publication was specifically and individually indicated to beincorporated by reference.

1. A panel of isolated biomarkers comprising N of the biomarkers listedin Tables 1 through
 63. 2. The panel of claim 1, wherein N is a numberselected from the group consisting of 2 to
 24. 3-6. (canceled)
 7. Amethod of determining probability for preterm birth in a pregnantfemale, the method comprising detecting a measurable feature of each ofN biomarkers selected from the biomarkers listed in Tables 1 through 63in a biological sample obtained from said pregnant female, and analyzingsaid measurable feature to determine the probability for preterm birthin said pregnant female.
 8. The method of claim 7, wherein saidmeasurable feature comprises fragments or derivatives of each of said Nbiomarkers selected from the biomarkers listed in Tables 1 through 63.9. The method of claim 7, wherein said detecting a measurable featurecomprises quantifying an amount of each of N biomarkers selected fromthe biomarkers listed in Tables 1 through 63, combinations or portionsand/or derivatives thereof in a biological sample obtained from saidpregnant female.
 10. (canceled)
 11. The method of claim 7, furthercomprising an initial step of providing a biomarker panel comprising Nof the biomarkers listed in Tables 1 through
 63. 12. The method of claim7, further comprising an initial step of providing a biological samplefrom the pregnant female. 13-14. (canceled)
 15. The method of claim 7,wherein N is a number selected from the group consisting of 2 to 24.16-37. (canceled)
 38. A method of predicting GAB, the method comprisingdetecting a measurable feature of each of N biomarkers selected from thebiomarkers listed in Tables 1 through 63 in a biological sample obtainedfrom a pregnant female, and analyzing said measurable feature to predictGAB.
 39. The method of claim 38, wherein said measurable featurecomprises fragments or derivatives of each of said N biomarkers selectedfrom the biomarkers listed in Tables 1 through
 63. 40. The method ofclaim 38, wherein said detecting a measurable feature comprisesquantifying an amount of each of N biomarkers selected from thebiomarkers listed in Tables 1 through 63, combinations or portionsand/or derivatives thereof in a biological sample obtained from saidpregnant female. 41-42. (canceled)
 43. The method of claim 38, furthercomprising an initial step of providing a biological sample from thepregnant female. 44-79. (canceled)
 80. A method of detecting and/orquantifying one or more biomarkers selected from biomarkers listed inTables 1 through 63 in a biological sample from a pregnant female, saidmethod comprising: a. obtaining said biological sample from a pregnantfemale; and b. detecting whether said one or more biomarkers are presentin the biological sample comprising subjecting the sample to massspectrometry, a capture agent or a combination thereof.